glm-5.3-flash vs mimo-v2.6-flash
Parameters, independent leaderboard coverage, real-task reports and open-weight availability are shown side by side; missing coverage is not a zero.
Parameters
| Comparison item | glm-5.3-flash | mimo-v2.6-flash |
|---|---|---|
| Model Type | LLM | LLM |
| Context window | 1,000,000 tokens | — |
| Maximum output | 128,000 tokens | — |
| Input/output modalities | text, image, video → text | — |
| Endpoint | openai · anthropic | openai · anthropic · openai-response |
| Open weights | Available | Available |
| License | MIT | MIT (declared in the model card metadata) |
Leaderboard coverage
Every independent board covering either model is retained; an em dash means that board has not published a figure for that model.
Real-task reports
glm-5.3-flash
- RemakeBench Launch 005: four Flash models on 14 fixtures — Fourteen fixtures spanning game building, 3D scenes, CAD, drawing and robot control, run on Qwen 3.8 Flash, DeepSeek V4.1 Flash, GLM 5.3 Flash and Gemini 3.8 Flash. Finding: No model won overall. GLM 5.3 Flash was the only model to pass the Apple-stem manipulation task and passed the single-turn Rubik's Cube, but did not complete the three-move extension and delivered no native geometry in Turbofan CAD. Limitation: Pass/fail labels are video judgments without a machine-readable validator, and single attempts do not establish reliability; the lab publishes no aggregate score or overall winner. GLM's Infinite Cathedral completion needed repeated user continuations because the endpoint stalled.
- GLM 5.3 Flash alone and with Jev on Halite 2 — Play the turn-based strategy game Halite 2. Finding: GLM 5.3 Flash alone beat Jev alone 82% of the time; the hybrid was 13× faster at 56% of the pure GLM API cost with a slight performance edge. Limitation: The author calls it a single example and among their first experiments with Jev; results may not carry over to other tasks.
- DeepSeek V4.1 Flash and GLM 5.3 Flash recreating two game menus — Recreate the Psychonauts 2 and Metroid Prime main menus as closely as possible to the originals. Finding: GLM 5.3 Flash used 134k and 111k tokens, a third to a quarter of DeepSeek V4.1 Flash's, and the author judged its menus clearly better on both games. Limitation: Which menu is closer to the original is the author's own judgement on two prompts, without a scoring rubric.
- DeepSeek V4.1 Flash and GLM-5.3-Flash on a Blender geometry task, run locally — Write a Blender script that builds a dodecahedron trapped inside a dodecahedron. Finding: GLM-5.3-Flash produced a correct mesh (zero intersections, containment verified in-script) and the nicer picture, but took 93 min 12 s and 132,250 tokens at 23.7 tok/s, against 20 min 15 s and 62,928 tokens for DeepSeek V4.1 Flash. Limitation: One local run per model on different hardware and precision: GLM ran as a third-party EXL3 quantisation on two DGX Sparks and DeepSeek as FP8 on four, so speed and token counts describe those builds, not the official weights or a hosted API.
- Three Flash models build the same koi pond locally — A koi pond build, run as a local head-to-head. Finding: All three finished cleanly with zero fixes, but GLM-5.3-Flash was slowest at 59 minutes and 90.9K tokens, against 30 minutes for MiMo-V2.6-Flash and 21 for DeepSeek V4.1 Flash; the author said it was the first of their tests where GLM was not the winner. Limitation: One local run per model; the post states neither the prompt nor the quantisation or runtime used.
mimo-v2.6-flash
- MiMo-V2.6-Flash, DeepSeek V4.1 Flash and Grok 4.7 on one game prompt — Build a playable browser game from a single prompt with Command Code's /design command. Finding: MiMo-V2.6-Flash scored 9/10 for $0.005, the cheapest run, with a playable one-shot game. DeepSeek V4.1 Flash also scored 9/10 at $0.0089; Grok 4.7 scored 8/10 at $0.20 and needed iterations. Limitation: One prompt rated by the author, whose profile lists work for Command Code, the tool that ran the test; there is no rubric and no repeated run.
- A senior engineer's security and git tasks with MiMo-V2.6 Pro and Flash — Create a branch and cherry-pick one commit in a sandbox whose git worktree turned out to be corrupted. Finding: MiMo-V2.6-Flash spent about 80k tokens on risky workarounds such as tampering with /tmp and mount --bind instead of diagnosing or recovering the worktree; the author concludes it falls well short of its benchmark placement and stays with DeepSeek V4.1 Flash and Qwen3.8-Flash. Limitation: One task per model, with the serving provider, quantisation and settings not stated; the post's title calls the series benchmaxxed.
- Three Flash models build the same koi pond locally — A koi pond build, run as a local head-to-head. Finding: All three finished cleanly with zero fixes; MiMo-V2.6-Flash took 30 minutes and 75.5K tokens, between DeepSeek V4.1 Flash (21 minutes, 53.3K) and GLM-5.3-Flash (59 minutes, 90.9K). Limitation: One local run per model; the post states neither the prompt nor the quantisation or runtime used.
- MiMo-V2.6-Flash on page and SVG tasks and a real app bug fix — Build pages explaining Chinese bagua culture and how a thorium molten-salt reactor works, draw Schrödinger's cat as an SVG, and fix a real bug in the author's app. Finding: The pages and SVGs were the best the author had seen, scoring 85–95 (the bagua page 95, against about 90 for DeepSeek's page in an earlier test), and all the tasks together cost about $0.50; but the bagua page took at least five times as long as DeepSeek's, the first attempt at it failed after 10–20 minutes, and a simple app bug fix stalled for an hour on tool-call errors. Limitation: One author's scores on a handful of tasks; the DeepSeek comparison rests on the author's earlier runs and estimates, and the author expects Xiaomi may fix the speed and tool-call problems.
- A MiMo-V2.6-Flash game build that needed steering — A browser game build the author meant to run zero-shot. Finding: The model thought for more than 11 minutes and got stuck in an overthinking loop while writing the file, so the author had to steer it several times; the result was solid, cost about $0.05, and scored 9.5/10 from the author, who said it did not feel like a Flash model for speed. Limitation: One task with several manual interventions, which the author says means it may not reflect what the model would produce on its own; the score is the author's.