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Its release_date follows Epoch, which re-dated this build from 2026-07-19, the Preview's announcement at WAIC, to 2026-08-02 between its 2026-08-25 and 2026-09-03 releases; Model Studio listed qwen3.8-max on 2026-08-02 as well. Alibaba Cloud's update notices of 2026-09-02 (www.aliyun.com/notice/118616 and the international Model Studio notice Update Notice for Qwen3.8-Max Models) state that from 10:00 Beijing time on 2026-09-05, subject to the actual change time, the qwen3.8-max model name automatically moved to the qwen3.8-max-0902 snapshot with billing unchanged. The name on sale here therefore now serves the Qwen3.8-Max-0902 row, and Model Studio lists no snapshot ID for this build, so it can no longer be called there. Every figure on this row belongs to this build: Artificial Analysis's Qwen3.8 Max (slug qwen3-8-max-0803), Epoch's Qwen 3.8 Max (dated 2026-08-02), SuperCLUE's Qwen3.8-Max(max) (evaluation published 2026-08-06), LMArena's qwen3.8-max (added to its Text Arena on 2026-08-02 per its changelog), LiveBench's Qwen 3.8 Max (quoted at the same figures since 2026-08-10, before the snapshot existed) and Vals's Qwen 3.8 Max (released 2026-08-03 per its model page). Artificial Analysis marked its Qwen3.8 Max row deprecated between the 2026-09-12 and 2026-09-21 reads; the leaderboard hides such rows under its default Status: Current filter, so this row's leaderboard figures are read with the Status filter set to All. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories. The exact build is absent from the Vals Index v2.2 cohort read on 2026-10-23; its former v2.1 figure is no longer quoted."},{"consensus":{"name":"muse-spark-1.3","slug":"muse-spark-1-3","rank":13,"score":57.1,"coverage":0.362,"source_count":11,"operator_count":4,"family_count":5,"specialty_count":5,"direct_anchors":10,"missing":[],"stability":{"from":12,"to":21,"fixedFrom":13,"fixedTo":22,"scenarios":56,"sensitive":true,"incomplete":0,"ordinalRank":15,"unavailable":0},"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text 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Epoch, which carried no row for it as of 2026-09-05, lists it as Muse Spark 1.3 (dated 2026-09-02) in the 2026-09-22 read. LMArena added muse-spark-1.3-max to its text board on 2026-09-13 per its leaderboard changelog; the row stands on 12,343 votes in its 2026-10-02 dataset publish. Previously served here as muse-spark-1.3-contributor, Meta's Contributor tier, whose terms let Meta train future models on the prompts and completions sent to it. That tier's reasoning_effort stops at xhigh: the LMArena and Artificial Analysis rows quoted here are the max-effort setting, which it does not offer; the LiveBench rows are xHigh, and Vals and Epoch name no effort setting. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories. The exact build is absent from the Vals Index v2.2 cohort read on 2026-10-23; its former v2.1 figure is no longer quoted. 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Alibaba Cloud's update notices of 2026-09-02 (www.aliyun.com/notice/118616 and the international Model Studio notice Update Notice for Qwen3.8-Max Models) state that from 10:00 Beijing time on 2026-09-05, subject to the actual change time, the qwen3.8-max model name automatically moved to this snapshot with billing unchanged. Alibaba published no completion notice; Artificial Analysis has since marked the earlier build deprecated. This row therefore links to qwen3.8-max, the name on sale here; the same snapshot is also sold under its pinned name qwen3.8-max-0902. Artificial Analysis and Epoch list it as Qwen3.8 Max (0902), SuperCLUE as Qwen3.8-Max-0902(max) (evaluation published 2026-09-10). LMArena added qwen3.8-max-0902 only to its Code Arena (changelog, 2026-09-01), which this page does not cite, and neither LiveBench nor Vals carries a 0902 row; the 2026-08-02 build's figures on the qwen3.8-max row are not reused 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The previously cited Vals Index V2 row is absent from the V2.1 board read on 2026-10-01, so its old V2 figure is no longer quoted. 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SpaceXAI. Artificial Analysis marked its Grok 4.5 (high) row deprecated between the 2026-09-12 and 2026-09-21 reads; the leaderboard hides such rows under its default Status: Current filter, so this row's leaderboard figures are read with the Status filter set to All. Released 2026-07-08 per xAI's announcement as published that day and its API release notes; the live announcement page now shows Jul 16, the date it was edited when the model reached the EU. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories. 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The vendor retired V4 Flash and V4 Flash Vision Exp that day and temporarily routes their old identifiers to V4.1 Flash; their historical leaderboard rows remain separate and none of their figures are reused here. Artificial Analysis, LiveBench and Vals all published distinct V4.1 Flash rows by 2026-09-12; Epoch (DeepSeek V4.1 Flash, dated 2026-09-09) and SuperCLUE (DeepSeek-V4.1-Flash(max), evaluation published 2026-09-11) carry one as of the 2026-09-22 read. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories. Historical 2026-09-10 checkpoint: the official deepseek-flash API now serves DeepSeek-V4.1-Flash-1017. This row keeps its original anchor and its own observations; the currently served build is listed separately. 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LMArena, LiveBench and Artificial Analysis all picked it up within days of release; the LMArena row is a ranked one, standing on 22,971 votes in its 2026-10-02 dataset publish. Epoch, SuperCLUE and Vals carried no row for it as of 2026-08-31. In the 2026-09-22 read Epoch lists it as GLM-5.3-Flash dated 2026-08-20, six days before Z.ai's release notes; the benchmark runs behind that figure are on the glm-5.3-flash model itself (Epoch's model versions glm-5.3-flash_max and glm-5.3-flash_high), so only the date differs. SuperCLUE lists GLM-5.3-Flash(max) with an evaluation published 2026-09-10, and Vals lists it as GLM 5.3 Flash, released 2026-08-26 per its model page. GLM-5.3's figures are not reused here. The previously cited Vals Index V2 row is absent from the V2.1 board read on 2026-10-01, so its old V2 figure is no longer quoted. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories."},{"consensus":{"name":"deepseek-v4-pro-0813","slug":"deepseek-v-4-pro-20260813","rank":29,"score":43.2,"coverage":0.368,"source_count":12,"operator_count":5,"family_count":7,"specialty_count":5,"direct_anchors":10,"missing":[],"stability":{"from":22,"to":31,"fixedFrom":24,"fixedTo":31,"scenarios":56,"sensitive":true,"incomplete":0,"ordinalRank":31,"unavailable":0},"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena 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Epoch added a DeepSeek V4 Pro 0813 row between the 2026-08-26 and 2026-08-31 snapshots, so the undated DeepSeek-V4-Pro figure is no longer borrowed for it. LMArena's 0813 row stands on 9,780 votes in its 2026-10-02 dataset publish. SuperCLUE announced on 2026-08-26 that it had added the official DeepSeek-V4-Pro; in the July 2026 edition's data file read on 2026-09-22 that row is labelled DeepSeek-V4-Pro-0813(max), with an evaluation published 2026-08-18, and the 64.40 row the board had labelled DeepSeek-V4-Pro(max) 预览版, now plain DeepSeek-V4-Pro(max), is the preview build, quoted on the deepseek-v4-pro row rather than here. 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Artificial Analysis lists Grok 4.7 (xhigh) and Grok 4.7 (high), both printing 46; the xhigh row is quoted because it is the highest effort setting and the higher score before rounding (46.4 against 46.3). 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OpenAI announced a limited partner preview of the GPT-5.6 series (Sol, Terra and Luna) on 2026-06-26 and made the models generally available on 2026-07-09, the post the preview page links as the launch; release_date follows the launch. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories. The exact build is absent from the Vals Index v2.2 cohort read on 2026-10-23; its former v2.1 figure is no longer 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DeepSeek retired V4 Flash on 2026-09-10 and its compatibility ID now routes to V4.1 Flash; this historical score row is not the currently served build and is not marked on sale. Artificial Analysis marked its DeepSeek V4 Flash 0731 (max) row deprecated between the 2026-09-12 and 2026-09-21 reads; the leaderboard hides such rows under its default Status: Current filter, so this row's leaderboard figures are read with the Status filter set to All. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories. 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LiveBench dropped this row in favour of the dated builds between the 2026-08-19 and 2026-08-26 snapshots, so its 71.6 is no longer quoted. SuperCLUE's DeepSeek-V4-Pro(max) row (64.40), which its July 2026 edition labelled 预览版, is quoted here from CA-971 on, overturning CA-605. CA-605 left it out because LMArena lists deepseek-v4-pro and deepseek-v4-pro-high-preview separately, but LMArena's own data gives those two rows the same checkpoint key (deepseek-v4-pro-ch1-text and deepseek-v4-pro-ch1-thinking-text) and links both to DeepSeek's 2026-04-24 announcement: they are one build in two modes, which DeepSeek's change log calls V4-Pro-Preview. Before the 2026-08-13 GA that build was the only one the deepseek-v4-pro API served, so an API evaluation published in the July edition can only be this row. SuperCLUE's data file has since dropped the 预览版 label and dates the row 2026.9.10, keeping the July figure. Artificial Analysis marked its DeepSeek V4 Pro (max) row deprecated between the 2026-09-12 and 2026-09-21 reads; the leaderboard hides such rows under its default Status: Current filter, so this row's leaderboard figures are read with the Status filter set to All. The exact build is absent from the Vals Index v2.2 cohort read on 2026-10-23; its former v2.1 figure is no longer quoted."},{"consensus":{"name":"gpt-6-luna","slug":"gpt-6-luna","rank":38,"score":32.4,"coverage":0.428,"source_count":13,"operator_count":5,"family_count":7,"specialty_count":6,"direct_anchors":10,"missing":[],"stability":{"from":25,"to":39,"fixedFrom":27,"fixedTo":39,"scenarios":56,"sensitive":true,"incomplete":0,"ordinalRank":39,"unavailable":0},"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text 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Epoch, which carried no row for it as of 2026-09-05, lists it as Qwen 3.8 27B (dated 2026-08-14) in the 2026-09-22 read. Artificial Analysis lists several effort settings; the first-listed xhigh row is quoted rather than a lower-effort sibling. The previously cited Vals Index V2 row is absent from the V2.1 board read on 2026-10-01, so its old V2 figure is no longer quoted. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories."},{"consensus":{"name":"MiniMax-M3","slug":"minimax-m-3","rank":40,"score":31.3,"coverage":0.34,"source_count":10,"operator_count":5,"family_count":5,"specialty_count":6,"direct_anchors":9,"missing":[],"stability":{"from":34,"to":40,"fixedFrom":39,"fixedTo":40,"scenarios":56,"sensitive":true,"incomplete":0,"ordinalRank":40,"unavailable":0},"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text 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categories."},{"consensus":{"name":"kimi-k3.1-pro","slug":"kimi-k3-1-pro","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"kimi-k3.1-pro","display_name":"Kimi K3.1 Pro","vendor":"Moonshot AI","origin":"cn","category":"text","release_date":"2026-10-23","on_chinaapi":true,"sources":[],"notes":"Released 2026-10-23, as dated in Kimi Code's official changelog (https://www.kimi.com/code/docs/en/kimi-code/whats-new.html). The official technical blog (https://www.kimi.ai/blog/kimi-k3-1-pro) identifies it as the first K3.1-series model, a post-trained version of K3 with a 1M-token context window, available in Kimi products and via kimi-k3.1-pro in the Kimi API. Full model weights are promised by 2026-11-04; that is a future release commitment, not evidence that weights are already public. The official Moonshot AI Hugging Face organization returned no K3.1 repository at this read. Highspeed is described as the same model capabilities at approximately 2-3x speed, so it is recorded as a serving variant rather than a second ranked model. No exact K3.1 Pro row is present in the 16 available consensus metrics checked on 2026-10-23; K3 and K2.x scores are not inherited and vendor-reported results do not supply independent evidence. Artificial Analysis is unavailable to consensus without its API key; absence here does not claim that no other evaluator has tested it. Listed in the public ChinaAPI pricing catalogue, verified 2026-10-24."},{"consensus":{"name":"MiniMax-M3.1-Flash","slug":"minimax-m-3-1-flash","rank":null,"score":null,"coverage":0.094,"source_count":3,"operator_count":3,"family_count":2,"specialty_count":3,"direct_anchors":9,"missing":["families"],"stability":null,"evidence":[{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"minimax-m-3-1-flash","value":1589.7463962339605,"lower":1576.367940183677,"upper":1603.1248522842438,"entry":"MiniMax-M3.1-Flash","configuration":"source_default:default@minimax-m3-1-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":2164},{"source":"mercor-apex-agents","unit":"mercor-apex-agents:loop-pass-1","url":"https://www.mercor.com/apex/apex-agents-leaderboard/","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-09-08T00:00:00.000Z","protocol":"{\"harnesses\":\"loop_truncated_tools_agent\",\"statistic\":\"pass-1\",\"dataAtKind\":\"benchmark-edition-publication\",\"datasetUrl\":\"https://huggingface.co/datasets/mercor/apex-agents-v1.1\",\"dataDateSource\":\"https://www.mercor.com/blog/introducing-apex-agents-1-1\",\"benchmarkVersion\":\"1.1\",\"comparisonSubject\":\"CONTROLLED_SYSTEM\",\"upstreamPublishedAt\":\"2026-09-08T00:00:00.000Z\",\"sourceOperator\":\"Mercor\",\"sourceFamily\":\"professional-work\",\"metricCount\":1}","source_name":"Mercor APEX-Agents 1.1","model":"minimax-m-3-1-flash","value":53.9,"lower":48.8,"upper":59,"entry":"minimax-m3p1-flash","configuration":"scaffolded:harness-loop-truncated-tools-agent+max+systemid-apex-agents-v1-1-loop-truncated-tools-agent@minimax-m3p1-flash","configuration_label":"Max 推理 · loop_truncated_tools_agent · apex-agents:v1.1:loop_truncated_tools_agent","selected":true,"selection_reason":"该来源对所有模型使用同一受控系统；按预先固定的推理档位优先级选择，配置明细保留，成绩归到基础模型。","samples":959},{"source":"vals-finance-agent","unit":"vals-finance-agent","url":"https://www.vals.ai/benchmarks/fabv2-1","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"valsTask\":\"finance-agent-v2-1\",\"benchmarkVersion\":\"2.1\",\"upstreamPublishedAt\":\"2026-10-22\",\"upstreamModelCount\":30,\"sourceOperator\":\"Vals AI\",\"sourceFamily\":\"professional-work\",\"metricCount\":1}","source_name":"Vals Finance Agent","model":"minimax-m-3-1-flash","value":58.826,"lower":56.756,"upper":60.896,"entry":"minimax/MiniMax-M3.1-flash","configuration":"first_party:max@minimax-minimax-m3-1-flash","configuration_label":"Max 推理","selected":true,"selection_reason":"按预先固定的规则，采用该来源可用的最高第一方推理档位；选择不参考跑分高低。","samples":null}],"excluded":[]},"name":"MiniMax-M3.1-Flash","display_name":"MiniMax M3.1 Flash","vendor":"MiniMax","origin":"cn","category":"text","release_date":"2026-10-19","on_chinaapi":true,"open_weights":{"url":"https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash","license":"MiniMax Community License","released_at":"2026-10-23","verified_at":"2026-10-23"},"sources":[{"leaderboard":"vals_index","metric":"Accuracy (GDP-weighted finance, coding, legal and tax)","value":"53.78","entry":"MiniMax-M3.1-Flash","url":"https://www.vals.ai/benchmarks/vals_index","retrieved_at":"2026-10-23","interval":"±1.07"}],"notes":"Announced 2026-10-19 in MiniMax's official release post (https://minimax.cn/blog/minimax-m31f). Official weights are available at https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash, verified 2026-10-23, under the MiniMax Community License. Native multimodal model for coding and agentic work; not an image generator. Only exact-build independent observations enter consensus; vendor-reported benchmark scores are not substituted. Listed in the public ChinaAPI pricing catalogue, verified 2026-10-24."},{"consensus":{"name":"mimo-v2.6-flash","slug":"mimo-v-2-6-flash","rank":null,"score":null,"coverage":0.214,"source_count":5,"operator_count":2,"family_count":2,"specialty_count":3,"direct_anchors":9,"missing":["families","operators"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"mimo-v-2-6-flash","value":1448.1035716010952,"lower":1442.0921150553786,"upper":1454.115028146812,"entry":"MiMo-V2.6-Flash","configuration":"source_default:default@mimo-v2-6-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":13730},{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"mimo-v-2-6-flash","value":1633.9955372073473,"lower":1624.822458138667,"upper":1643.1686162760277,"entry":"MiMo-V2.6-Flash","configuration":"source_default:default@mimo-v2-6-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":5681},{"source":"vals-finance-agent","unit":"vals-finance-agent","url":"https://www.vals.ai/benchmarks/fabv2-1","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"valsTask\":\"finance-agent-v2-1\",\"benchmarkVersion\":\"2.1\",\"upstreamPublishedAt\":\"2026-10-22\",\"upstreamModelCount\":30,\"sourceOperator\":\"Vals AI\",\"sourceFamily\":\"professional-work\",\"metricCount\":1}","source_name":"Vals Finance Agent","model":"mimo-v-2-6-flash","value":63.316,"lower":61.232,"upper":65.4,"entry":"xiaomi/mimo-v2.6-flash","configuration":"source_default:default@xiaomi-mimo-v2-6-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":null},{"source":"arena-creative-writing","unit":"arena-creative-writing","url":"https://arena.ai/leaderboard/text/creative-writing","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"creative_writing\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Creative Writing","model":"mimo-v-2-6-flash","value":1392.9138475963864,"lower":1380.6706545394266,"upper":1405.157040653346,"entry":"MiMo-V2.6-Flash","configuration":"source_default:default@mimo-v2-6-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":2741},{"source":"arena-vision","unit":"arena-vision","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-19T00:00:00.000Z","protocol":"{\"arenaConfig\":\"vision_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Vision Style-Controlled","model":"mimo-v-2-6-flash","value":1244.5332459478107,"lower":1233.645808796727,"upper":1255.4206830988942,"entry":"MiMo-V2.6-Flash","configuration":"source_default:default@mimo-v2-6-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":3618}],"excluded":[]},"name":"mimo-v2.6-flash","display_name":"MiMo-V2.6-Flash","vendor":"Xiaomi","origin":"cn","category":"text","release_date":"2026-09-22","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_text","metric":"Arena score (Elo)","value":"1452","entry":"mimo-v2.6-flash","url":"https://arena.ai/leaderboard/text","retrieved_at":"2026-10-05","interval":"±8","samples":6053},{"leaderboard":"lmarena_text_chinese","metric":"Arena score (Elo)","value":"1502","entry":"mimo-v2.6-flash","url":"https://arena.ai/leaderboard/text/chinese","retrieved_at":"2026-10-05","interval":"±27","samples":466},{"leaderboard":"lmarena_text_coding","metric":"Arena score (Elo)","value":"1521","entry":"mimo-v2.6-flash","url":"https://arena.ai/leaderboard/text/coding","retrieved_at":"2026-10-05","interval":"±15","samples":1508},{"leaderboard":"vals_index","metric":"Accuracy (GDP-weighted finance, coding, legal and tax)","value":"54.83","entry":"MiMo V2.6 Flash","url":"https://www.vals.ai/benchmarks/vals_index","retrieved_at":"2026-10-23","interval":"±1.11"}],"notes":"Released and open-sourced 2026-09-22 per Xiaomi's release record (MiMo-V2.6 Series Release). The 2026-10-01 Vals Index v2.1 read independently covers this model, replacing the previously quoted vendor self-reported DeepSWE figure."},{"consensus":{"name":"mimo-v2.6-pro-ultraspeed","slug":"mimo-v-2-6-pro-ultraspeed","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"mimo-v2.6-pro-ultraspeed","display_name":"MiMo-V2.6-Pro-Ultraspeed","vendor":"Xiaomi","origin":"cn","category":"text","release_date":"2026-09-22","on_chinaapi":true,"sources":[],"notes":"Xiaomi's high-speed serving mode of MiMo-V2.6-Pro, released 2026-09-22. The vendor states flagship V2.6-Pro performance at up to 20x the output speed but publishes no separate figures, and no board lists it separately, so MiMo-V2.6-Pro's scores are not reused here."},{"consensus":{"name":"step-5-preview","slug":"step-5-preview","rank":null,"score":null,"coverage":0.214,"source_count":5,"operator_count":2,"family_count":2,"specialty_count":3,"direct_anchors":9,"missing":["families","operators"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"step-5-preview","value":1447.682422338529,"lower":1441.0219686129528,"upper":1454.3428760641054,"entry":"Step 5 Preview","configuration":"source_default:default@step-5-preview","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":9792},{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"step-5-preview","value":1568.0681899848569,"lower":1558.5806766314763,"upper":1577.5557033382374,"entry":"Step 5 Preview (High)","configuration":"first_party:high@step-5-preview-high","configuration_label":"High 推理","selected":true,"selection_reason":"按预先固定的规则，采用该来源可用的最高第一方推理档位；选择不参考跑分高低。","samples":5135},{"source":"vals-finance-agent","unit":"vals-finance-agent","url":"https://www.vals.ai/benchmarks/fabv2-1","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"valsTask\":\"finance-agent-v2-1\",\"benchmarkVersion\":\"2.1\",\"upstreamPublishedAt\":\"2026-10-22\",\"upstreamModelCount\":30,\"sourceOperator\":\"Vals AI\",\"sourceFamily\":\"professional-work\",\"metricCount\":1}","source_name":"Vals Finance Agent","model":"step-5-preview","value":58.9,"lower":56.846,"upper":60.954,"entry":"stepfun/step-5-preview","configuration":"source_default:default@stepfun-step-5-preview","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":null},{"source":"arena-creative-writing","unit":"arena-creative-writing","url":"https://arena.ai/leaderboard/text/creative-writing","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"creative_writing\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Creative Writing","model":"step-5-preview","value":1409.1602555348131,"lower":1395.2798228861584,"upper":1423.0406881834676,"entry":"Step 5 Preview","configuration":"source_default:default@step-5-preview","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":2061},{"source":"arena-vision","unit":"arena-vision","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-19T00:00:00.000Z","protocol":"{\"arenaConfig\":\"vision_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Vision Style-Controlled","model":"step-5-preview","value":1247.1751302786683,"lower":1232.0164871773625,"upper":1262.3337733799742,"entry":"Step 5 Preview","configuration":"source_default:default@step-5-preview","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":1649}],"excluded":[]},"name":"step-5-preview","display_name":"Step 5 Preview","vendor":"StepFun","origin":"cn","category":"text","release_date":"2026-09-20","on_chinaapi":true,"open_weights":{"url":"https://huggingface.co/collections/stepfun-ai/step-5-preview","license":"StepFun Model License 1.0","verified_at":"2026-10-23"},"sources":[{"leaderboard":"aa_index","metric":"Intelligence Index","value":"44","entry":"Step 5 Preview","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_speed","metric":"Median output tokens/s","value":"83","entry":"Step 5 Preview","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"},{"leaderboard":"aa_gdpval","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","value":"53","entry":"Step 5 Preview","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_tbench_v40","metric":"Agentic Coding \u0026 Terminal Use (%)","value":"33","entry":"Step 5 Preview","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_mlcr","metric":"Medical Long Context Reasoning (%)","value":"16.7","entry":"Step 5 Preview","url":"https://artificialanalysis.ai/evaluations/mlcr-aa","retrieved_at":"2026-09-22"}],"notes":"StepFun's announcement page prints no date; it says the model is released today and cites Artificial Analysis results published as of 2026-09-20, and reports dated that day already quote the release, which fixes the release date. Official BF16, FP8 and NVFP4 weights are now available in the StepFun collection, verified 2026-10-23 (https://huggingface.co/collections/stepfun-ai/step-5-preview). The StepFun Model License 1.0 has additional attribution and commercial-license conditions; it is not an unmodified Apache-2.0 license. Weight publication does not create a new model release or additional consensus ranks. Vals lists it as Step 5 Preview, released 2026-09-28 per its model page; the release date above follows StepFun's announcement. The exact build is absent from the Vals Index v2.2 cohort read on 2026-10-23; its former v2.1 figure is no longer quoted."},{"consensus":{"name":"hy4-preview","slug":"hy-4-preview","rank":null,"score":null,"coverage":0.09,"source_count":3,"operator_count":3,"family_count":3,"specialty_count":2,"direct_anchors":9,"missing":["categories"],"stability":null,"evidence":[{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"hy-4-preview","value":1631.2200784490426,"lower":1621.5723158553617,"upper":1640.8678410427235,"entry":"Hy4 preview","configuration":"source_default:default@hy4-preview","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":4785},{"source":"vals-finance-agent","unit":"vals-finance-agent","url":"https://www.vals.ai/benchmarks/fabv2-1","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"valsTask\":\"finance-agent-v2-1\",\"benchmarkVersion\":\"2.1\",\"upstreamPublishedAt\":\"2026-10-22\",\"upstreamModelCount\":30,\"sourceOperator\":\"Vals AI\",\"sourceFamily\":\"professional-work\",\"metricCount\":1}","source_name":"Vals Finance Agent","model":"hy-4-preview","value":61.623,"lower":59.564,"upper":63.681999999999995,"entry":"tencent/hy4-preview","configuration":"source_default:default@tencent-hy4-preview","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":null},{"source":"taptap-maker","unit":"taptap-maker","url":"https://maker.taptap.cn/leaderboard/","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-18T00:00:00.000Z","protocol":"{\"editionId\":\"2026-10-18-v6-voxel\",\"datasetVersion\":\"0.2.3\",\"datasetHash\":\"de38ba84\",\"officialBoard\":\"main_board_l2\",\"upstreamPublishedAt\":\"2026-10-18\",\"comparisonSubject\":\"SYSTEM_CONFIGURATION\",\"sourceOperator\":\"TapTap Maker\",\"sourceFamily\":\"game-development\",\"metricCount\":1}","source_name":"TapTap Maker Benchmark","model":"hy-4-preview","value":0.7248,"lower":0.7248,"upper":0.7248,"entry":"hy4-preview","configuration":"first_party:high@hy4-preview","configuration_label":"High 推理","selected":true,"selection_reason":"按预先固定的规则，采用该来源可用的最高第一方推理档位；选择不参考跑分高低。","samples":null}],"excluded":[]},"name":"hy4-preview","display_name":"Hy4-preview","vendor":"Tencent","origin":"cn","category":"text","release_date":"2026-08-28","on_chinaapi":true,"sources":[{"leaderboard":"vals_index","metric":"Accuracy (GDP-weighted finance, coding, legal and tax)","value":"53.21","entry":"Hy4 Preview","url":"https://www.vals.ai/benchmarks/vals_index","retrieved_at":"2026-10-23","interval":"±1.13"}],"notes":"Tencent announced and open-sourced Hy4 preview on 2026-08-28. The Vals Index lists it as Hy4 Preview (tencent/hy4-preview); Artificial Analysis, LMArena, LiveBench and Epoch carried no row for it as of 2026-09-21, and those figures are left blank. Hy3 scores and AutoEval results are not attributed to this row."},{"consensus":{"name":"qwen3.8-flash","slug":"qwen-3-8-flash-next","rank":null,"score":null,"coverage":0.06,"source_count":2,"operator_count":2,"family_count":2,"specialty_count":1,"direct_anchors":9,"missing":["sources","families","operators","categories"],"stability":null,"evidence":[{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"qwen-3-8-flash-next","value":1628.0236765856525,"lower":1620.1901120337432,"upper":1635.857241137562,"entry":"Qwen3.8-Flash-Next","configuration":"source_default:default@qwen3-8-flash-next","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":8797},{"source":"taptap-maker","unit":"taptap-maker","url":"https://maker.taptap.cn/leaderboard/","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-18T00:00:00.000Z","protocol":"{\"editionId\":\"2026-10-18-v6-voxel\",\"datasetVersion\":\"0.2.3\",\"datasetHash\":\"de38ba84\",\"officialBoard\":\"main_board_l2\",\"upstreamPublishedAt\":\"2026-10-18\",\"comparisonSubject\":\"SYSTEM_CONFIGURATION\",\"sourceOperator\":\"TapTap Maker\",\"sourceFamily\":\"game-development\",\"metricCount\":1}","source_name":"TapTap Maker Benchmark","model":"qwen-3-8-flash-next","value":0.7603,"lower":0.7464,"upper":0.7742,"entry":"qwen3.8-flash","configuration":"first_party:xhigh@qwen3-8-flash","configuration_label":"xHigh 推理","selected":true,"selection_reason":"按预先固定的规则，采用该来源可用的最高第一方推理档位；选择不参考跑分高低。","samples":null}],"excluded":[]},"name":"qwen3.8-flash","display_name":"Qwen3.8-Flash","vendor":"Alibaba","origin":"cn","category":"text","release_date":"2026-08-26","on_chinaapi":true,"sources":[{"leaderboard":"aa_index","metric":"Intelligence Index","value":"40","entry":"Qwen3.8-Flash-Next","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"superclue","metric":"总分 (overall)","value":"66.41","entry":"Qwen3.8-Flash(max)","url":"https://www.superclueai.com/homepage","retrieved_at":"2026-10-04"},{"leaderboard":"aa_speed","metric":"Median output tokens/s","value":"54","entry":"Qwen3.8-Flash-Next","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"},{"leaderboard":"aa_gdpval","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","value":"56","entry":"Qwen3.8-Flash-Next","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_tbench_v40","metric":"Agentic Coding \u0026 Terminal Use (%)","value":"25","entry":"Qwen3.8-Flash-Next","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"}],"notes":"The boards list this model under its open-weight release name, Qwen3.8-Flash-Next (released 2026-08-26 per the Qwen team). The vendor's announcement states that the production version, with a 1M default context and built-in tools, is served under the name Qwen3.8-Flash, which is the qwen3.8-flash API on sale here since 2026-09-04; the two rows are joined on that statement, not on the row name. Artificial Analysis now prints 40 without an estimated marker (read 2026-09-21). SuperCLUE lists it under the API name itself, Qwen3.8-Flash(max), evaluated through the API with an evaluation published 2026-09-10, so that figure needs no join. Neither Epoch, LMArena nor Vals carried a row as of 2026-09-05. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories."},{"consensus":{"name":"deepseek-v4-flash-vision-exp","slug":"deepseek-v-4-flash-vision-exp","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"deepseek-v4-flash-vision-exp","display_name":"DeepSeek V4 Flash Vision Exp","vendor":"DeepSeek","origin":"cn","category":"text","release_date":"2026-08-21","on_chinaapi":false,"sources":[{"leaderboard":"aa_index","metric":"Intelligence Index","value":"35","entry":"DeepSeek V4 Flash Vision (max)","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_speed","metric":"Median output tokens/s","value":"231","entry":"DeepSeek V4 Flash Vision (max)","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"},{"leaderboard":"aa_gdpval","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","value":"52","entry":"DeepSeek V4 Flash Vision (max)","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_tbench_v40","metric":"Agentic Coding \u0026 Terminal Use (%)","value":"12","entry":"DeepSeek V4 Flash Vision (max)","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"}],"notes":"DeepSeek's experimental vision tier, announced in the vendor's change log on 2026-08-21 as model='deepseek-v4-flash-vision-exp'. LiveBench names its row with the vendor's -Exp suffix and Artificial Analysis drops it, but DeepSeek publishes only one vision tier, so both rows are this model. LMArena, Vals, SuperCLUE and Epoch carry no row for it, and the sibling flash figures are not reused. DeepSeek retired this tier on 2026-09-10 and its compatibility ID now routes to V4.1 Flash. It is absent from the public catalogue read on 2026-09-12 and is retained here as a historical evaluation row without an on-sale badge. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories."},{"consensus":{"name":"hy3","slug":"hy-3","rank":null,"score":null,"coverage":0.124,"source_count":3,"operator_count":1,"family_count":1,"specialty_count":1,"direct_anchors":9,"missing":["families","operators","categories"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"hy-3","value":1453.7970900098853,"lower":1447.810100904093,"upper":1459.7840791156777,"entry":"Hy3","configuration":"source_default:default@hy3","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":13220},{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"hy-3","value":1506.0134281028777,"lower":1497.7221350023299,"upper":1514.3047212034255,"entry":"Hy3","configuration":"source_default:default@hy3","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":6403},{"source":"arena-creative-writing","unit":"arena-creative-writing","url":"https://arena.ai/leaderboard/text/creative-writing","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"creative_writing\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Creative Writing","model":"hy-3","value":1424.2541928288358,"lower":1412.2459293081672,"upper":1436.2624563495046,"entry":"Hy3","configuration":"source_default:default@hy3","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":2655}],"excluded":[]},"name":"hy3","display_name":"Hunyuan Hy3","vendor":"Tencent","origin":"cn","category":"text","release_date":"2026-07-06","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_text","metric":"Arena score (Elo)","value":"1456","entry":"hy3","url":"https://arena.ai/leaderboard/text","retrieved_at":"2026-10-05","interval":"±7","samples":10476},{"leaderboard":"aa_index","metric":"Intelligence Index","value":"25","entry":"Hy3","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"superclue","metric":"总分 (overall)","value":"62.13","entry":"Hy3(high)","url":"https://www.superclueai.com/homepage","retrieved_at":"2026-10-04"},{"leaderboard":"lmarena_text_chinese","metric":"Arena score (Elo)","value":"1509","entry":"hy3","url":"https://arena.ai/leaderboard/text/chinese","retrieved_at":"2026-10-05","interval":"±21","samples":779},{"leaderboard":"lmarena_text_coding","metric":"Arena score (Elo)","value":"1500","entry":"hy3","url":"https://arena.ai/leaderboard/text/coding","retrieved_at":"2026-10-05","interval":"±11","samples":2921},{"leaderboard":"aa_speed","metric":"Median output tokens/s","value":"87","entry":"Hy3","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"},{"leaderboard":"aa_gdpval","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","value":"27","entry":"Hy3","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_tbench_v40","metric":"Agentic Coding \u0026 Terminal Use (%)","value":"1","entry":"Hy3","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"}],"notes":""},{"consensus":{"name":"LongCat-2.0","slug":"longcat-2-0","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"LongCat-2.0","display_name":"LongCat-2.0","vendor":"Meituan","origin":"cn","category":"text","release_date":"2026-06-30","on_chinaapi":true,"sources":[{"leaderboard":"aa_index","metric":"Intelligence Index","value":"19","entry":"LongCat 2.0","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"superclue","metric":"总分 (overall)","value":"54.22","entry":"LongCat-2.0","url":"https://www.superclueai.com/homepage","retrieved_at":"2026-10-04"},{"leaderboard":"aa_gdpval","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","value":"18","entry":"LongCat 2.0","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_tbench_v40","metric":"Agentic Coding \u0026 Terminal Use (%)","value":"0","entry":"LongCat 2.0","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"}],"notes":"Artificial Analysis no longer printed an output-speed value for this row on 2026-09-12, so the old figure was removed rather than retained without a live source."},{"consensus":{"name":"doubao-seed-2-1-pro-260628","slug":"doubao-seed-2-1-pro","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"doubao-seed-2-1-pro-260628","display_name":"Doubao-Seed-2.1-pro","vendor":"ByteDance","origin":"cn","category":"text","release_date":"2026-06-28","on_chinaapi":true,"sources":[{"leaderboard":"superclue","metric":"总分 (overall)","value":"65.94","entry":"Doubao-Seed-2.1-pro(high)","url":"https://www.superclueai.com/homepage","retrieved_at":"2026-10-04"},{"leaderboard":"vendor_card","metric":"Terminal Bench 2.1","value":"71.0","entry":"vendor-published figure","url":"https://seed.bytedance.com/seed2_1","retrieved_at":"2026-08-10"}],"notes":""},{"consensus":{"name":"doubao-seed-2-1-turbo-260628","slug":"doubao-seed-2-1-turbo","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"doubao-seed-2-1-turbo-260628","display_name":"Doubao-Seed-2.1-turbo","vendor":"ByteDance","origin":"cn","category":"text","release_date":"2026-06-28","on_chinaapi":true,"sources":[{"leaderboard":"vendor_card","metric":"Terminal Bench 2.1","value":"67.6","entry":"vendor-published figure","url":"https://seed.bytedance.com/seed2_1","retrieved_at":"2026-08-10"}],"notes":"No independent board in this snapshot covers it; the figure shown is the vendor's own. The vendor writes the name without the 260628 snapshot suffix we serve it under."},{"consensus":{"name":"qwen3.7-plus","slug":"qwen-3-7-plus","rank":null,"score":null,"coverage":0.228,"source_count":6,"operator_count":2,"family_count":4,"specialty_count":3,"direct_anchors":10,"missing":["operators"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"qwen-3-7-plus","value":1455.7042471746377,"lower":1451.3763931612818,"upper":1460.0321011879935,"entry":"Qwen3.7-Plus","configuration":"source_default:default@qwen3-7-plus","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":42058},{"source":"arena-creative-writing","unit":"arena-creative-writing","url":"https://arena.ai/leaderboard/text/creative-writing","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"creative_writing\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Creative Writing","model":"qwen-3-7-plus","value":1430.8784596174369,"lower":1423.258823097157,"upper":1438.4980961377169,"entry":"Qwen3.7-Plus","configuration":"source_default:default@qwen3-7-plus","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":7839},{"source":"arena-vision","unit":"arena-vision","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-19T00:00:00.000Z","protocol":"{\"arenaConfig\":\"vision_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Vision Style-Controlled","model":"qwen-3-7-plus","value":1263.3077120307532,"lower":1256.6059526828433,"upper":1270.009471378663,"entry":"Qwen3.7-Plus","configuration":"source_default:default@qwen3-7-plus","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":14212},{"source":"epoch-gpqa","unit":"epoch-gpqa","url":"https://epoch.ai/benchmarks/gpqa-diamond","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-19T22:38:32.000Z","protocol":"{\"dataAtKind\":\"latest-evaluation\",\"benchmarkFile\":\"gpqa_diamond.csv\",\"scoringField\":\"mean_score\",\"upstreamPublishedAt\":\"2026-10-19T22:38:32.000Z\",\"attribution\":\"Epoch AI · AI Benchmarking Hub · CC BY 4.0\",\"sourceOperator\":\"Epoch AI\",\"metricCount\":1}","source_name":"GPQA 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Removed from ChinaAPI on 2026-10-24 after Xiaomi retired this model on 2026-10-21; historical benchmark evidence is retained."},{"consensus":{"name":"step-3.5-flash-2603","slug":"step-3-5-flash-2603","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"step-3.5-flash-2603","display_name":"Step 3.5 Flash 2603","vendor":"StepFun","origin":"cn","category":"text","release_date":"2026-04-02","on_chinaapi":true,"sources":[{"leaderboard":"aa_index","metric":"Intelligence Index","value":"17*","entry":"Step 3.5 Flash 2603","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_speed","metric":"Median output tokens/s","value":"118","entry":"Step 3.5 Flash 2603","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"}],"notes":"StepFun's agent-optimised variant of step-3.5-flash, whose reasoning_effort takes only low and high. Released 2026-04-02 per StepFun's announcement on its X account (\"Step 3.5 Flash 2603 just shipped!\"). Artificial Analysis lists it as Step 3.5 Flash 2603 (released 2026-04-02 on its model page) and marks the row deprecated; the leaderboard hides such rows under its default Status: Current filter, so its figures are read with the Status filter set to All, and its Intelligence Index is an estimate (*). LMArena carries no 2603 row: its step-3.5-flash row is the base build and is not reused here. 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(Elo)","value":"1482","entry":"qwen3.6-plus","url":"https://arena.ai/leaderboard/text/chinese","retrieved_at":"2026-10-05","interval":"±12","samples":2651},{"leaderboard":"lmarena_text_coding","metric":"Arena score (Elo)","value":"1496","entry":"qwen3.6-plus","url":"https://arena.ai/leaderboard/text/coding","retrieved_at":"2026-10-05","interval":"±6","samples":14656}],"notes":"The previously cited Vals Index V2 row is absent from the V2.1 board read on 2026-10-01, so its old V2 figure is no longer quoted. LiveBench 1.0 scores were withdrawn on 2026-10-23 after the site moved them into its historical-release view and launched the incompatible LiveBench 2.0 categories."},{"consensus":{"name":"MiniMax-M2.7","slug":"minimax-m-2-7","rank":null,"score":null,"coverage":0.124,"source_count":3,"operator_count":1,"family_count":1,"specialty_count":1,"direct_anchors":9,"missing":["families","operators","categories"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"minimax-m-2-7","value":1414.9702489524907,"lower":1411.6543855855514,"upper":1418.28611231943,"entry":"MiniMax-M2.7","configuration":"source_default:default@minimax-m2-7","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":87731},{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"minimax-m-2-7","value":1398.332645072846,"lower":1392.5468177421628,"upper":1404.118472403529,"entry":"MiniMax-M2.7","configuration":"source_default:default@minimax-m2-7","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":15977},{"source":"arena-creative-writing","unit":"arena-creative-writing","url":"https://arena.ai/leaderboard/text/creative-writing","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"creative_writing\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Creative Writing","model":"minimax-m-2-7","value":1364.072416827921,"lower":1358.0310011922788,"upper":1370.113832463563,"entry":"MiniMax-M2.7","configuration":"source_default:default@minimax-m2-7","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":15100}],"excluded":[]},"name":"MiniMax-M2.7","display_name":"MiniMax-M2.7","vendor":"MiniMax","origin":"cn","category":"text","release_date":"2026-03-18","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_text","metric":"Arena score (Elo)","value":"1415","entry":"minimax-m2.7","url":"https://arena.ai/leaderboard/text","retrieved_at":"2026-10-05","interval":"±3","samples":79944},{"leaderboard":"epoch_eci","metric":"General ECI","value":"146","entry":"MiniMax-M2.7","url":"https://epoch.ai/eci","retrieved_at":"2026-10-04","interval":"(138 - 148)"},{"leaderboard":"lmarena_text_chinese","metric":"Arena score (Elo)","value":"1447","entry":"minimax-m2.7","url":"https://arena.ai/leaderboard/text/chinese","retrieved_at":"2026-10-05","interval":"±9","samples":5108},{"leaderboard":"lmarena_text_coding","metric":"Arena score (Elo)","value":"1480","entry":"minimax-m2.7","url":"https://arena.ai/leaderboard/text/coding","retrieved_at":"2026-10-05","interval":"±5","samples":22889}],"notes":"The previously cited Vals Index V2 row is absent from the V2.1 board read on 2026-10-01, so its old V2 figure is no longer quoted."},{"consensus":{"name":"glm-5-turbo","slug":"glm-5-turbo","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"glm-5-turbo","display_name":"GLM-5-Turbo","vendor":"Zhipu AI (Z.ai)","origin":"cn","category":"text","release_date":"2026-03-16","on_chinaapi":false,"sources":[],"notes":"No independent board in this snapshot carries a row for it."},{"consensus":{"name":"step-3.5-flash","slug":"step-3-5-flash","rank":null,"score":null,"coverage":0.1,"source_count":2,"operator_count":1,"family_count":1,"specialty_count":0,"direct_anchors":9,"missing":["sources","families","operators","categories"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"step-3-5-flash","value":1392.9703531883067,"lower":1389.418730266936,"upper":1396.5219761096773,"entry":"Step-3.5-Flash","configuration":"source_default:default@step-3-5-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":60329},{"source":"arena-creative-writing","unit":"arena-creative-writing","url":"https://arena.ai/leaderboard/text/creative-writing","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"creative_writing\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Creative Writing","model":"step-3-5-flash","value":1345.122224422255,"lower":1338.3572088408323,"upper":1351.8872400036776,"entry":"Step-3.5-Flash","configuration":"source_default:default@step-3-5-flash","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":9784}],"excluded":[]},"name":"step-3.5-flash","display_name":"Step 3.5 Flash","vendor":"StepFun","origin":"cn","category":"text","release_date":"2026-02-02","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_text","metric":"Arena score (Elo)","value":"1393","entry":"step-3.5-flash","url":"https://arena.ai/leaderboard/text","retrieved_at":"2026-10-05","interval":"±4","samples":60207},{"leaderboard":"aa_index","metric":"Intelligence Index","value":"17*","entry":"Step 3.5 Flash","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"lmarena_text_chinese","metric":"Arena score (Elo)","value":"1432","entry":"step-3.5-flash","url":"https://arena.ai/leaderboard/text/chinese","retrieved_at":"2026-10-05","interval":"±10","samples":3658},{"leaderboard":"lmarena_text_coding","metric":"Arena score (Elo)","value":"1449","entry":"step-3.5-flash","url":"https://arena.ai/leaderboard/text/coding","retrieved_at":"2026-10-05","interval":"±6","samples":15168},{"leaderboard":"aa_speed","metric":"Median output tokens/s","value":"126","entry":"Step 3.5 Flash","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"}],"notes":"StepFun's platform documentation lists step-3.5-flash as the base version and step-3.5-flash-2603 as an agent-optimised variant built from it; the 2603 build shipped on 2026-04-02 and has its own row here. LMArena added step-3.5-flash to its text board on 2026-02-10, linking the original open weights, seven weeks before 2603 shipped, so its three text-board rows are this build (60,207 votes on the overall board in its 2026-10-02 dataset publish). Artificial Analysis lists this build as Step 3.5 Flash (released 2026-02-02 on its model page) and marks the row deprecated; the leaderboard hides such rows under its default Status: Current filter, so its figures are read with the Status filter set to All, and its Intelligence Index is an estimate (*). The vendor's own SWE-bench Verified figure (74.4) that stood here while no independent board was quoted has been removed. LiveBench, Epoch, Vals and SuperCLUE carry no row for it."},{"consensus":{"name":"agnes-2.0-flash","slug":"agnes-2-0-flash","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"agnes-2.0-flash","display_name":"Agnes 2.0 Flash","vendor":"Agnes AI","origin":"cn","category":"text","on_chinaapi":false,"sources":[{"leaderboard":"vendor_card","metric":"Claw-Eval Pass^3","value":"60.9%","entry":"vendor-published figure","url":"https://agnes-ai.com/en/docs/agnes-20-flash","retrieved_at":"2026-08-10"}],"notes":"No independent board in this snapshot covers it; the figure shown is the vendor's own. Retired from sale 2026-09-03 (CA-654): the vendor deprecated it in favour of agnes-2.5-flash; kept as a ranked row with on_chinaapi false so the roster count and maintained.at still describe the 2026-08-31 board read."},{"consensus":{"name":"agnes-2.5-flash","slug":"agnes-2-5-flash","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"agnes-2.5-flash","display_name":"Agnes 2.5 Flash","vendor":"Agnes AI","origin":"cn","category":"text","on_chinaapi":true,"sources":[],"notes":"Artificial Analysis carries a different build of this family (Agnes 2.5 Pro Alpha, 40) and the vendor publishes its own figures only as a chart image, so there is no number here that can be quoted."},{"consensus":{"name":"agnes-3.0-flash","slug":"agnes-3-0-flash","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"agnes-3.0-flash","display_name":"Agnes 3.0 Flash","vendor":"Agnes AI","origin":"cn","category":"text","on_chinaapi":true,"sources":[{"leaderboard":"aa_index","metric":"Intelligence Index","value":"36*","entry":"Agnes 3.0 Flash","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_gdpval","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","value":"53","entry":"Agnes 3.0 Flash","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_tbench_v40","metric":"Agentic Coding \u0026 Terminal Use (%)","value":"7","entry":"Agnes 3.0 Flash","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"}],"notes":"Artificial Analysis lists Agnes 3.0 Flash separately from the 2.5 family. Its Intelligence Index is currently estimated, so the trailing * is retained exactly as the board prints it. Artificial Analysis no longer printed an output-speed value for this row on 2026-09-21 (the column reads --), so the 238 tokens/s figure was removed rather than retained without a live source; the index, GDPval-AA and Terminal-Bench figures are from the 2026-09-21 board read."},{"consensus":{"name":"deepseek-v4-flash","slug":"deepseek-v-4-flash-preview","rank":null,"score":null,"coverage":0.16,"source_count":4,"operator_count":2,"family_count":2,"specialty_count":1,"direct_anchors":9,"missing":["families","operators","categories"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"deepseek-v-4-flash-preview","value":1438.6554496886292,"lower":1434.5493088769829,"upper":1442.7615905002754,"entry":"DeepSeek-V4-Flash Preview 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Writing","model":"deepseek-v-4-flash-preview","value":1407.933417383682,"lower":1400.420604110208,"upper":1415.4462306571559,"entry":"DeepSeek-V4-Flash","configuration":"source_default:default@deepseek-v4-flash","configuration_label":"来源默认配置","selected":false,"selection_reason":"该配置已保留供核对，但固定优先级低于本指标的代表配置。","samples":8579}]},"name":"deepseek-v4-flash","display_name":"DeepSeek V4 Flash","vendor":"DeepSeek","origin":"cn","category":"text","on_chinaapi":false,"sources":[{"leaderboard":"lmarena_text","metric":"Arena score (Elo)","value":"1436","entry":"deepseek-v4-flash","url":"https://arena.ai/leaderboard/text","retrieved_at":"2026-10-05","interval":"±4","samples":51850},{"leaderboard":"epoch_eci","metric":"General ECI","value":"146","entry":"DeepSeek-V4-Flash","url":"https://epoch.ai/eci","retrieved_at":"2026-10-04","interval":"(144 - 148)"},{"leaderboard":"lmarena_text_chinese","metric":"Arena score (Elo)","value":"1471","entry":"deepseek-v4-flash","url":"https://arena.ai/leaderboard/text/chinese","retrieved_at":"2026-10-05","interval":"±11","samples":2984},{"leaderboard":"lmarena_text_coding","metric":"Arena score (Elo)","value":"1484","entry":"deepseek-v4-flash","url":"https://arena.ai/leaderboard/text/coding","retrieved_at":"2026-10-05","interval":"±6","samples":15244}],"notes":"The pre-0731 build. LMArena still lists this build and carries no 0731 row in its 2026-10-02 dataset publish; LiveBench dropped its row between the 2026-08-19 and 2026-08-26 snapshots, so its 65.5 is no longer quoted. Epoch lists this build as DeepSeek-V4-Flash, dated 2026-04-24, separately from its DeepSeek V4 Flash 0731 row."},{"consensus":{"name":"doubao-seed-evolving","slug":"doubao-seed-evolving","rank":null,"score":null,"coverage":0.036,"source_count":1,"operator_count":1,"family_count":1,"specialty_count":1,"direct_anchors":5,"missing":["sources","families","operators","categories"],"stability":null,"evidence":[{"source":"taptap-maker","unit":"taptap-maker","url":"https://maker.taptap.cn/leaderboard/","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-18T00:00:00.000Z","protocol":"{\"editionId\":\"2026-10-18-v6-voxel\",\"datasetVersion\":\"0.2.3\",\"datasetHash\":\"de38ba84\",\"officialBoard\":\"main_board_l2\",\"upstreamPublishedAt\":\"2026-10-18\",\"comparisonSubject\":\"SYSTEM_CONFIGURATION\",\"sourceOperator\":\"TapTap Maker\",\"sourceFamily\":\"game-development\",\"metricCount\":1}","source_name":"TapTap Maker Benchmark","model":"doubao-seed-evolving","value":0.7164,"lower":0.6932,"upper":0.7395,"entry":"doubao-seed-evolving","configuration":"first_party:high@doubao-seed-evolving","configuration_label":"High 推理","selected":true,"selection_reason":"按预先固定的规则，采用该来源可用的最高第一方推理档位；选择不参考跑分高低。","samples":null}],"excluded":[]},"name":"doubao-seed-evolving","display_name":"Doubao-Seed-Evolving","vendor":"ByteDance","origin":"cn","category":"text","on_chinaapi":true,"sources":[],"notes":"Doubao publishes Seed Evolving as a rolling model under the stable doubao-seed-evolving API ID, so capabilities can change without a dated version suffix. No independent score could be verified for this exact model on the boards cited by this snapshot as of 2026-09-12; Seed 2.1 scores are not reused."},{"consensus":{"name":"glm-5v-turbo","slug":"glm-5-v-turbo","rank":null,"score":null,"coverage":0.184,"source_count":4,"operator_count":1,"family_count":1,"specialty_count":2,"direct_anchors":9,"missing":["families","operators","categories"],"stability":null,"evidence":[{"source":"arena-text","unit":"arena-text","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Text Style-Controlled","model":"glm-5-v-turbo","value":1433.9223996040687,"lower":1427.4901328244273,"upper":1440.3546663837103,"entry":"GLM-5V-Turbo","configuration":"source_default:default@glm-5v-turbo","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":10477},{"source":"arena-webdev","unit":"arena-webdev","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"webdev\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena WebDev","model":"glm-5-v-turbo","value":1401.747603237029,"lower":1388.516071279464,"upper":1414.9791351945937,"entry":"GLM-5V-Turbo","configuration":"source_default:default@glm-5v-turbo","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":2400},{"source":"arena-creative-writing","unit":"arena-creative-writing","url":"https://arena.ai/leaderboard/text/creative-writing","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-22T00:00:00.000Z","protocol":"{\"arenaConfig\":\"text_style_control\",\"arenaCategory\":\"creative_writing\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Creative Writing","model":"glm-5-v-turbo","value":1407.5461223622303,"lower":1393.2743859191096,"upper":1421.817858805351,"entry":"GLM-5V-Turbo","configuration":"source_default:default@glm-5v-turbo","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":1968},{"source":"arena-vision","unit":"arena-vision","url":"https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-10-19T00:00:00.000Z","protocol":"{\"arenaConfig\":\"vision_style_control\",\"arenaCategory\":\"overall\",\"datasetRevision\":\"5acd3fc8c7f1693ba2f4d74103aca3159db58657\",\"sourceOperator\":\"LMArena\",\"sourceFamily\":\"arena-preference\",\"metricCount\":1}","source_name":"Arena Vision Style-Controlled","model":"glm-5-v-turbo","value":1230.0377895189233,"lower":1224.5556949642917,"upper":1235.5198840735552,"entry":"GLM-5V-Turbo","configuration":"source_default:default@glm-5v-turbo","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":42757}],"excluded":[]},"name":"glm-5v-turbo","display_name":"GLM-5V-Turbo","vendor":"Zhipu AI (Z.ai)","origin":"cn","category":"text","on_chinaapi":false,"sources":[{"leaderboard":"lmarena_text","metric":"Arena score (Elo)","value":"1433","entry":"glm-5v-turbo","url":"https://arena.ai/leaderboard/text","retrieved_at":"2026-10-05","interval":"±6","samples":10436},{"leaderboard":"lmarena_text_chinese","metric":"Arena score (Elo)","value":"1474","entry":"glm-5v-turbo","url":"https://arena.ai/leaderboard/text/chinese","retrieved_at":"2026-10-05","interval":"±21","samples":773},{"leaderboard":"lmarena_text_coding","metric":"Arena score (Elo)","value":"1488","entry":"glm-5v-turbo","url":"https://arena.ai/leaderboard/text/coding","retrieved_at":"2026-10-05","interval":"±11","samples":2917}],"notes":"Vision-language model. LMArena's text board now carries a glm-5v-turbo row (10,436 votes in its 2026-10-02 dataset publish); Epoch does not score it."},{"consensus":{"name":"ling-3-1-flash","slug":"ling-3-1-flash","rank":null,"score":null,"coverage":0,"source_count":0,"operator_count":0,"family_count":0,"specialty_count":0,"direct_anchors":0,"missing":["sources","families","operators","categories","directAnchors"],"stability":null,"evidence":[],"excluded":[]},"name":"ling-3-1-flash","display_name":"Ling-3.1-flash","vendor":"InclusionAI","origin":"cn","category":"text","on_chinaapi":false,"open_weights":{"url":"https://huggingface.co/inclusionAI/Ling-3.1-flash","license":"MIT","verified_at":"2026-10-23"},"sources":[],"notes":"Official inclusionAI weights and MIT license verified 2026-10-23 at https://huggingface.co/inclusionAI/Ling-3.1-flash. A 560B-total/25B-active native hybrid reasoning model with up to 1M context. A substantiated vendor announcement date has not been established here, so the release-date cell is left empty; the weight-repository creation date is not substituted. No exact-model observations were found in the sources available to this consensus run. Artificial Analysis is unavailable to consensus without its API key; a third-party index or the vendor's self-reported scores cannot fill that gap. Not present in the public ChinaAPI pricing catalogue read on 2026-10-23."},{"consensus":{"name":"qwen3.8-2.4t-a95b","slug":"qwen-3-8-2-4-t-a-95-b","rank":null,"score":null,"coverage":0.036,"source_count":1,"operator_count":1,"family_count":1,"specialty_count":1,"direct_anchors":6,"missing":["sources","families","operators","categories"],"stability":null,"evidence":[{"source":"eq-creative","unit":"eq-creative","url":"https://eqbench.com/creative_writing.html","fetched_at":"2026-10-23T19:29:14.402Z","published_at":"2026-09-24T07:57:16Z","protocol":"{\"dataAtKind\":\"score-data-commit\",\"dataCommit\":\"108382e3f5017dce6f90c643e6bb4842825f62df\",\"upstreamPublishedAt\":\"2026-09-24T07:57:16Z\",\"benchmarkVersion\":\"creative-writing-v3\",\"sourceOperator\":\"EQ-Bench\",\"sourceFamily\":\"judged-creative-writing\",\"metricCount\":1}","source_name":"Creative Writing v3","model":"qwen-3-8-2-4-t-a-95-b","value":1842.5,"lower":null,"upper":null,"entry":"Qwen/Qwen3.8-2.4T-A95B","configuration":"source_default:default@qwen-qwen3-8-2-4t-a95b","configuration_label":"来源默认配置","selected":true,"selection_reason":"该来源没有区分推理档位，采用其官方默认配置。","samples":null}],"excluded":[]},"name":"qwen3.8-2.4t-a95b","display_name":"Qwen3.8-2.4T-A95B","vendor":"Alibaba","origin":"cn","category":"text","on_chinaapi":true,"sources":[{"leaderboard":"aa_index","metric":"Intelligence Index","value":"40","entry":"Qwen3.8 2.4T A95B","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_speed","metric":"Median output tokens/s","value":"38","entry":"Qwen3.8 2.4T A95B","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-22"},{"leaderboard":"aa_gdpval","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","value":"55","entry":"Qwen3.8 2.4T A95B","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_tbench_v40","metric":"Agentic Coding \u0026 Terminal Use (%)","value":"11","entry":"Qwen3.8 2.4T A95B","url":"https://artificialanalysis.ai/leaderboards/models","retrieved_at":"2026-09-21"},{"leaderboard":"aa_mlcr","metric":"Medical Long Context Reasoning (%)","value":"0.0","entry":"Qwen3.8 2.4T A95B","url":"https://artificialanalysis.ai/evaluations/mlcr-aa","retrieved_at":"2026-09-22"}],"notes":"The open-weight Qwen3.8-2.4T-A95B release has its own Artificial Analysis row. Qwen identifies Qwen3.8-Max as a production version based on this model with additional features; the two catalogue models remain separate here, and Max scores from other boards are not reused. Artificial Analysis prints MLCR-AA 0.0 for this release, with no breakdown, against 19.4 and 20.0 for the two Qwen3.8-Max builds."}],"new_models":[{"model":"kimi-k3.1-pro","comparisons":[]},{"model":"MiniMax-M3.1-Flash","comparisons":[{"model":"MiniMax-M3","units":["arena-webdev","mercor-apex-agents:loop-pass-1","vals-finance-agent"]},{"model":"MiniMax-M2.7","units":["arena-webdev"]}]}]},{"id":"image","primary_source":"lmarena_t2i","sources":["lmarena_t2i","lmarena_image_edit","aa_image_t2i","aa_image_edit"],"models":[{"name":"gpt-image-2.5-sunburst","display_name":"GPT Image 2.5 Sunburst","vendor":"OpenAI","origin":"intl","category":"image","release_date":"2026-09-08","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1424","entry":"gpt-image-2.5-sunburst","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±8","samples":10884},{"leaderboard":"lmarena_image_edit","metric":"Arena score (Elo)","value":"1522","entry":"gpt-image-2.5-sunburst","url":"https://arena.ai/leaderboard/image-edit","retrieved_at":"2026-10-05","interval":"±5","samples":47289},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"1179","entry":"GPT Image 2.5 Sunburst (max)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-11/11","samples":5159},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1167","entry":"GPT Image 2.5 Sunburst (max)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-10/10","samples":5216}],"notes":"Sunburst and Flare are distinct builds; their scores are not interchangeable.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"210.7","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2.5 Sunburst (max)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"210.7","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2.5 Sunburst (max)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"},{"kind":"generation_time","task":"text_to_image","value":"112.476080179214","unit":"seconds","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2.5 Sunburst (max), OpenAI","conditions":"1024×1024 or nearest supported; 1 image; 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their scores are not interchangeable.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"210.7","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2.5 Flare (max)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"210.7","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2.5 Flare (max)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"},{"kind":"generation_time","task":"text_to_image","value":"53.0124175548553","unit":"seconds","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2.5 Flare (max), OpenAI","conditions":"1024×1024 or nearest supported; 1 image; 3-day median; 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Artificial Analysis quotes high quality. These are different test configurations, not interchangeable scores.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"211.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2 (high)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"211.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"OpenAI","entry":"GPT Image 2 (high)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"gemini-3.1-flash-image","display_name":"Gemini 3.1 Flash Image","vendor":"Google","origin":"intl","category":"image","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1261","entry":"gemini-3.1-flash-image (nano-banana-2) [web-search]","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±4","samples":53228},{"leaderboard":"lmarena_image_edit","metric":"Arena score (Elo)","value":"1387","entry":"gemini-3.1-flash-image (nano-banana-2) [web-search]","url":"https://arena.ai/leaderboard/image-edit","retrieved_at":"2026-10-05","interval":"±3","samples":216640},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"1122","entry":"Nano Banana 2 (Gemini 3.1 Flash Image)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-8/8","samples":16711},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1103","entry":"Nano Banana 2 (Gemini 3.1 Flash Image)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-9/9","samples":13522}],"notes":"Arena identifies a web-search-enabled entry; Artificial Analysis does not identify that condition in its row label. Do not assume identical configurations.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"67.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Google","entry":"Nano Banana 2 (Gemini 3.1 Flash Image)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"67.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Google","entry":"Nano Banana 2 (Gemini 3.1 Flash Image)","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"doubao-seedream-5-0-pro-260628","display_name":"Doubao Seedream 5.0 Pro","vendor":"ByteDance","origin":"cn","category":"image","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1256","entry":"seedream-5.0-pro","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±4","samples":85690},{"leaderboard":"lmarena_image_edit","metric":"Arena score (Elo)","value":"1394","entry":"seedream-5.0-pro","url":"https://arena.ai/leaderboard/image-edit","retrieved_at":"2026-10-05","interval":"±3","samples":270020},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"1081","entry":"Seedream 5.0 Pro","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-8/8","samples":12814},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1100","entry":"Seedream 5.0 Pro","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-9/9","samples":12053}],"notes":"The 260628 Pro SKU is distinct from the 260128 Lite SKU. Scores quote the arena's seedream-5.0-pro rows, not seedream-5.0-lite.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"90.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"ByteDance Seed","entry":"Seedream 5.0 Pro","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"90.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"ByteDance Seed","entry":"Seedream 5.0 Pro","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"qwen-image-3.0-pro","display_name":"Qwen Image 3.0 Pro","vendor":"Alibaba","origin":"cn","category":"image","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1256","entry":"qwen-image-3.0-pro","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±6","samples":11520},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"1084","entry":"Qwen-Image-3.0-Pro","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-10/10","samples":5896},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1076","entry":"Qwen-Image-3.0-Pro","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-9/9","samples":12051}],"notes":"No Qwen Image 3.0 Pro row on the Arena image-edit board as read from LMArena's dataset on 2026-10-05. The qwen-image-2.0-pro-2026-06-22 row is an older build and is not reused here.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"40.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Alibaba","entry":"Qwen-Image-3.0-Pro","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"40.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Alibaba","entry":"Qwen-Image-3.0-Pro","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"flux-2-pro","display_name":"FLUX.2 Pro","vendor":"Black Forest Labs","origin":"intl","category":"image","release_date":"2025-11-25","on_chinaapi":false,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1154","entry":"flux-2-pro","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±3","samples":205540},{"leaderboard":"lmarena_image_edit","metric":"Arena score (Elo)","value":"1245","entry":"flux-2-pro","url":"https://arena.ai/leaderboard/image-edit","retrieved_at":"2026-10-05","interval":"±3","samples":624352},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"1009","entry":"FLUX.2 [pro]","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-8/8","samples":9794},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1006","entry":"FLUX.2 [pro]","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-7/7","samples":8015}],"notes":"","reference_metrics":[{"kind":"price","task":"text_to_image","value":"30.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Black Forest Labs","entry":"FLUX.2 [pro]","conditions":"1024×1024; 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creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"40.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"ByteDance Seed","entry":"Seedream 4.5","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"doubao-seedream-5-0-260128","display_name":"Doubao Seedream 5.0 Lite","vendor":"ByteDance","origin":"cn","category":"image","release_date":"2026-01-28","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1138","entry":"seedream-5.0-lite","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±3","samples":123178},{"leaderboard":"lmarena_image_edit","metric":"Arena score (Elo)","value":"1294","entry":"seedream-5.0-lite","url":"https://arena.ai/leaderboard/image-edit","retrieved_at":"2026-10-05","interval":"±3","samples":446300},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"999","entry":"Seedream 5.0 Lite","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-9/9","samples":5027},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1050","entry":"Seedream 5.0 Lite","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-10/10","samples":4912}],"notes":"The 260128 API SKU is Seedream 5.0 Lite. Scores quote the arena's seedream-5.0-lite rows; the distinct 260628 Pro SKU has its own row. The original rank anchor is preserved.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"35.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"ByteDance Seed","entry":"Seedream 5.0 Lite","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"35.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"ByteDance Seed","entry":"Seedream 5.0 Lite","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"wan2.7-image-pro","display_name":"Wan 2.7 Image Pro","vendor":"Alibaba","origin":"cn","category":"image","release_date":"2026-04-01","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1103","entry":"wan2.7-image-pro","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±5","samples":30229},{"leaderboard":"lmarena_image_edit","metric":"Arena score (Elo)","value":"1303","entry":"wan2.7-image-pro","url":"https://arena.ai/leaderboard/image-edit","retrieved_at":"2026-10-05","interval":"±4","samples":43992},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"980","entry":"Wan 2.7 Pro","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-9/9","samples":5059},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1039","entry":"Wan 2.7 Pro","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-10/10","samples":4833}],"notes":"","reference_metrics":[{"kind":"price","task":"text_to_image","value":"64.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Alibaba","entry":"Wan 2.7 Pro","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"}]},{"name":"wan2.7-image","display_name":"Wan 2.7 Image","vendor":"Alibaba","origin":"cn","category":"image","release_date":"2026-04-01","on_chinaapi":true,"sources":[{"leaderboard":"lmarena_t2i","metric":"Arena score (Elo)","value":"1101","entry":"wan2.7-image","url":"https://arena.ai/leaderboard/text-to-image","retrieved_at":"2026-10-05","interval":"±5","samples":30621},{"leaderboard":"lmarena_image_edit","metric":"Arena score (Elo)","value":"1301","entry":"wan2.7-image","url":"https://arena.ai/leaderboard/image-edit","retrieved_at":"2026-10-05","interval":"±4","samples":44814},{"leaderboard":"aa_image_t2i","metric":"Elo","value":"977","entry":"Wan 2.7","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-9/9","samples":5029},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1033","entry":"Wan 2.7","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-9/9","samples":6291}],"notes":"","reference_metrics":[{"kind":"price","task":"text_to_image","value":"26.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Alibaba","entry":"Wan 2.7","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"26.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Alibaba","entry":"Wan 2.7","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"step-image-edit-2","display_name":"Step Image Edit 2","vendor":"StepFun","origin":"cn","category":"image","on_chinaapi":false,"sources":[{"leaderboard":"aa_image_t2i","metric":"Elo","value":"810","entry":"Step Image Edit 2","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13","interval":"-10/10","samples":2593},{"leaderboard":"aa_image_edit","metric":"Elo","value":"1008","entry":"Step Image Edit 2","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-10/10","samples":4235}],"notes":"No row on the LMArena image boards at the time of this snapshot; the arena carries an older StepFun build (step1x-edit, 998) that is a different model. Artificial Analysis evidence is now quoted separately for the identified task and exact entry.","reference_metrics":[{"kind":"price","task":"text_to_image","value":"3.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"StepFun","entry":"Step Image Edit 2","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","retrieved_at":"2026-09-13"},{"kind":"price","task":"image_editing","value":"3.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"StepFun","entry":"Step Image Edit 2","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"agnes-image-2.0-flash","display_name":"Agnes Image 2.0 Flash","vendor":"Agnes AI","origin":"cn","category":"image","on_chinaapi":true,"sources":[{"leaderboard":"aa_image_edit","metric":"Elo","value":"1017","entry":"Agnes Image 2.0 Flash","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13","interval":"-10/10","samples":3713}],"notes":"No row on the LMArena image boards at the time of this snapshot. Artificial Analysis evidence is now quoted separately for the identified task and exact entry.","reference_metrics":[{"kind":"price","task":"image_editing","value":"3.0","unit":"USD / 1,000 images","operator":"Artificial Analysis","provider":"Sapiens AI","entry":"Agnes Image 2.0 Flash","conditions":"1024×1024; creator API; default settings (AA pricing footnote)","url":"https://artificialanalysis.ai/image/leaderboard/editing","retrieved_at":"2026-09-13"}]},{"name":"agnes-image-2.1-flash","display_name":"Agnes Image 2.1 Flash","vendor":"Agnes AI","origin":"cn","category":"image","on_chinaapi":true,"sources":[],"notes":"No row on the LMArena image boards at the time of this snapshot."},{"name":"agnes-image-2.5-flash","display_name":"Agnes Image 2.5 Flash","vendor":"Agnes AI","origin":"cn","category":"image","on_chinaapi":true,"sources":[],"notes":"No Agnes Image 2.5 Flash row on either Arena image board as read from LMArena's dataset on 2026-10-05; no independent score is substituted."},{"name":"image-01","display_name":"MiniMax image-01","vendor":"MiniMax","origin":"cn","category":"image","on_chinaapi":false,"sources":[],"notes":"No row on the LMArena image boards at the time of this snapshot."},{"name":"step-2x-large","display_name":"Step 2X Large","vendor":"StepFun","origin":"cn","category":"image","on_chinaapi":false,"sources":[],"notes":"No row on the LMArena image boards at the time of this snapshot; the arena carries an older StepFun build (step1x-edit, 998) that is a different model."}],"quality_coverage":{"models":13,"total":17,"boards":4,"operators":2}},{"id":"video","primary_source":"lmarena_t2v","sources":["lmarena_t2v","lmarena_i2v","aa_video_t2v_audio","aa_video_i2v_audio"],"models":[{"name":"gemini-omni-flash-video","display_name":"Gemini Omni Flash (video)","vendor":"Google","origin":"intl","category":"video","on_chinaapi":false,"sources":[{"leaderboard":"lmarena_t2v","metric":"Arena score (Elo)","value":"1513","entry":"gemini-omni-flash","url":"https://arena.ai/leaderboard/text-to-video","retrieved_at":"2026-10-05","interval":"±9","samples":26576},{"leaderboard":"lmarena_i2v","metric":"Arena score (Elo)","value":"1465","entry":"gemini-omni-flash","url":"https://arena.ai/leaderboard/image-to-video","retrieved_at":"2026-10-05","interval":"±6","samples":87155},{"leaderboard":"aa_video_t2v_audio","metric":"Elo","value":"1238","entry":"Gemini Omni Flash","url":"https://artificialanalysis.ai/video/leaderboard/text-to-video","retrieved_at":"2026-09-13","interval":"-6/6","samples":16372},{"leaderboard":"aa_video_i2v_audio","metric":"Elo","value":"1181","entry":"Gemini Omni Flash","url":"https://artificialanalysis.ai/video/leaderboard/image-to-video","retrieved_at":"2026-09-13","interval":"-7/7","samples":11592}],"notes":"","reference_metrics":[{"kind":"price","task":"text_to_video_audio","value":"6.00","unit":"USD / video minute","operator":"Artificial Analysis","provider":"Google","entry":"Gemini Omni Flash","conditions":"1080p; 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Each rating is rounded half-up to a whole number and its interval is rating_upper minus rating, as arena.ai prints them; the dataset carries no Preliminary badge, so each citation records its row's vote count instead, and row names follow the dataset, which can trail a rename on arena.ai","licence":"CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), as labelled on the dataset card (https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset)","retrieved_at":"2026-10-05","scene":"chinese","updated_at":"2026-10-02"},{"id":"lmarena_text_coding","name":"LMArena Text Arena · Coding","operator":"LMArena (arena.ai)","metric":"Arena score (Elo)","url":"https://arena.ai/leaderboard/text/coding","edition":"Hugging Face dataset lmarena-ai/leaderboard-dataset (text_style_control, category coding), published 2026-10-02, revision 46919c467f7f. 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Rows Artificial Analysis marks deprecated are read with the leaderboard's Status filter set to All (CA-948)","retrieved_at":"2026-09-22","scene":"speed"},{"id":"aa_gdpval","name":"Artificial Analysis · GDPval-AA v2.1","operator":"Artificial Analysis","metric":"Agentic Real-World Work Tasks, (Elo-500)/2000 (%)","url":"https://artificialanalysis.ai/leaderboards/models","edition":"GDPval-AA v2.1, live board, read 2026-09-22. 220 agentic task-completion tasks with file outputs, ranked pairwise by a panel of three frontier LLM judges; since v2.1 the Elo scale is anchored to DeepSeek V4.1 Flash (max) at 1600 and fitted with a Crowd-BT model, so its figures are not comparable with the v2 figures this page quoted from its 2026-09-12 read. The column prints clamp((Elo-500)/2000). It carries 10% of the Agents category inside Intelligence Index v4.3.2, so this column is a component of the AA Intelligence Index shown as an individual source, not an independent operator. Rows Artificial Analysis marks deprecated are read with the leaderboard's Status filter set to All (CA-948). The column is hidden until the leaderboard's Intelligence group is expanded","retrieved_at":"2026-09-22","scene":"agent_work"},{"id":"aa_tbench_v40","name":"Artificial Analysis · Terminal-Bench v4.0","operator":"Artificial Analysis","metric":"Agentic Coding \u0026 Terminal Use (%)","url":"https://artificialanalysis.ai/leaderboards/models","edition":"Terminal-Bench 4.0 (66 tasks), run by Artificial Analysis with the mini-swe-agent harness, pass@1 averaged over 3 repeats per task; read 2026-09-22. When this column replaced the benchmark's own board on 2026-09-07 the methodology page named the harness as mini-SWE-agent v2.4.6; on 2026-09-21 it and the evaluation page name mini-swe-agent without a version, and every figure quoted before then read back unchanged. One harness for every model, so the column compares models rather than model-plus-best-scaffold — which is why it replaced the benchmark's own board, whose rows are agent × model and covered one Chinese model out of 34 (CA-788, overturning CA-734). It carries 10% of the Coding category inside Intelligence Index v4.3.2, so this column is a component of the AA Intelligence Index shown as an individual source, not an independent operator. Rows Artificial Analysis marks deprecated are read with the leaderboard's Status filter set to All (CA-948). The column is hidden until the leaderboard's Intelligence group is expanded","retrieved_at":"2026-09-22","scene":"agentic"},{"id":"aa_mlcr","name":"Artificial Analysis · MLCR-AA","operator":"Artificial Analysis","metric":"Medical Long Context Reasoning (%)","url":"https://artificialanalysis.ai/evaluations/mlcr-aa","edition":"MLCR-AA, live board, read 2026-09-22. Artificial Analysis marks it a standalone evaluation that is NOT part of Intelligence Index v4.3 — unlike the GDPval-AA v2 and Terminal-Bench v4.0 columns, this one is not a component of the AA Intelligence Index shown as an individual source, only the same operator. The underlying benchmark is Wisedocs' open MLCR (Wisedocs-AI/medical-long-context-reasoning): synthetic medical records of roughly 25,000-64,000 tokens, graded across six tiers from locating a single fact to expert-level clinical synthesis. It measures multi-document reasoning over long records, not medical capability in general. The main leaderboard carries no column for it; the figures were first read off the evaluation page's chart (2026-09-07) and since 2026-09-22 from the per-model pages' payload, which carries every model the chart can show (CA-956)","retrieved_at":"2026-09-22","scene":"medical"},{"id":"aa_image_t2i","name":"Artificial Analysis Text To Image","operator":"Artificial Analysis","metric":"Elo","url":"https://artificialanalysis.ai/image/leaderboard/text-to-image","edition":"live board; exact row settings retained","retrieved_at":"2026-09-13","task":"text_to_image"},{"id":"aa_image_edit","name":"Artificial Analysis Editing","operator":"Artificial Analysis","metric":"Elo","url":"https://artificialanalysis.ai/image/leaderboard/editing","edition":"live board; exact row settings retained","retrieved_at":"2026-09-13","task":"image_editing"},{"id":"aa_video_t2v_audio","name":"Artificial Analysis Text To Video · With Audio","operator":"Artificial Analysis","metric":"Elo","url":"https://artificialanalysis.ai/video/leaderboard/text-to-video","edition":"live board; with audio pool; exact row settings retained","retrieved_at":"2026-09-13","task":"text_to_video_audio"},{"id":"aa_video_i2v_audio","name":"Artificial Analysis Image To Video · With Audio","operator":"Artificial Analysis","metric":"Elo","url":"https://artificialanalysis.ai/video/leaderboard/image-to-video","edition":"live board; with audio pool; exact row settings retained","retrieved_at":"2026-09-13","task":"image_to_video_audio"}]},"success":true}