glm-5.3-flash vs qwen3.8-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 | qwen3.8-flash |
|---|---|---|
| Model Type | LLM | LLM |
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Maximum output | 128,000 tokens | — |
| Input/output modalities | text, image, video → text | text, image, video → text |
| Endpoint | openai · anthropic | anthropic · openai |
| Open weights | Available | Unavailable |
| License | MIT | Proprietary hosted model |
Leaderboard coverage
Every independent board covering either model is retained; an em dash means that board has not published a figure for that model.
A row marked as retrieved on different dates holds two readings taken on different days; a board re-fits or changes version as a whole between readings, so those two figures are not directly comparable.
| Evaluation | glm-5.3-flash | qwen3.8-flash |
|---|---|---|
| LMArena Text Arena — Arena score (Elo) | 1473 ±5 | — |
| Artificial Analysis Intelligence Index — Intelligence Index | 42 | 40 |
| SuperCLUE 智能指数 — 总分 (overall) | 68.10 | 66.41 |
| Epoch Capabilities Index (ECI) — General ECI | 152 (149 - 154) | — |
| Vals Index — Accuracy (GDP-weighted finance, coding, legal and tax) | 50.86 ±1.25 | — |
| LMArena Text Arena · Chinese — Arena score (Elo) | 1529 ±15 | — |
| LMArena Text Arena · Coding — Arena score (Elo) | 1523 ±8 | — |
| Artificial Analysis · Output Speed — Median output tokens/s | 65 | 54 |
| Artificial Analysis · GDPval-AA v2.1 — Agentic Real-World Work Tasks, (Elo-500)/2000 (%) | 57 | 56 |
| Artificial Analysis · Terminal-Bench v4.0 — Agentic Coding & Terminal Use (%) Retrieved on different dates | 33 (retrieved 2026-09-21) | 25 (retrieved 2026-09-22) |
| Artificial Analysis · MLCR-AA — Medical Long Context Reasoning (%) | 51.1 | — |
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.
- AI Coding Daily LLM Coding Leaderboard — Implement and harden production-shaped projects in several stacks, including a Laravel app, a Go service and a React/TypeScript app, from the same prompts. Finding: GLM-5.3-Flash at max reasoning scored 42.82 ($0.02 and 8 min 54 s per run in OpenCode), 38th of 47 rows and well below GLM-5.3 at 49.92. Limitation: One author's benchmark whose code-quality half is graded by a judge model; rows run in different harnesses, the page is updated as models are added (read on 2026-09-24, 47 rows), and the author sells premium tutorials and advertising.
- kzhu's six-question LLM test leaderboard — Six questions scored out of 10: constrained sentence writing, two reasoning puzzles (replaced by pelican and compound-bow SVG animations in version 2.2), a browser OS with a space shooter, a 3D racing game and a Trello-style board. Finding: GLM-5.3-Flash scored 54/60 on version 2.1 in zcode, with every reasoning answer right and the best recent space shooter the author had seen, but 45 after re-running the two version-2.2 SVG questions in Pi, where the pelican sank below the ring and the bow pointed backwards, taking over 20 minutes against under 10 for DeepSeek. Limitation: One author's scores on six questions; rows use different harnesses and test versions (2.1 or 2.2), and a few rows' table total differs by one point from the author's note.
qwen3.8-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. The lab's editorial preference put Qwen 3.8 Flash ahead in several game and 3D-scene rounds, such as the interactive voxel diorama, but it did not pass the single-turn Rubik's Cube ($0.2616, 48 min 35 s) and timed out on Turbofan CAD without any geometry. 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. Two Qwen results are still pending a judge, and its reasoning setting is unreported outside the campaign runs.
- AI Coding Daily LLM Coding Leaderboard — Implement and harden production-shaped projects in several stacks, including a Laravel app, a Go service and a React/TypeScript app, from the same prompts. Finding: Qwen 3.8 Flash at max reasoning scored 47.22 ($0.04 and 8 min 38 s per run in OpenCode), 28th of 47 rows. Limitation: One author's benchmark whose code-quality half is graded by a judge model; rows run in different harnesses, the page is updated as models are added (read on 2026-09-24, 47 rows), and the author sells premium tutorials and advertising.
- kzhu's six-question LLM test leaderboard — Six questions scored out of 10: constrained sentence writing, two reasoning puzzles (replaced by pelican and compound-bow SVG animations in version 2.2), a browser OS with a space shooter, a 3D racing game and a Trello-style board. Finding: Qwen 3.8 Flash scored 51/60 on version 2.1 in Claude Code: both maths puzzles right, but many small coding flaws, such as an overflowing browser-OS pop-up, a racing game that ends on the first crash and off-centre Trello buttons. Limitation: One author's scores on six questions; rows use different harnesses and test versions (2.1 or 2.2), and a few rows' table total differs by one point from the author's note.