Qwen3 235B A22B Instruct 2507 — Benchmarks
Benchmark scores for Qwen3 235B A22B Instruct 2507 aggregated from public leaderboards (9 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.
- #56 of 100 open models
- 9 boards · updated Oct 2026
- 100 = average open model
- Hardware requirements →
Qwen3 235B A22B Instruct 2507 reasoning benchmarks
Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.
1.3%
1.3%
median 11.8%open leader 72.9%
Overall best: GPT 6 Astra Max 95.0%
22nd percentile · #15 of 19 open · #189 of 222 all
IndependentEpoch AI ·
11.0%
11.0%
median 65.3%open leader 94.5%
Overall best: Claude Fable 5 (xhigh) 98.5%
17th percentile · #16 of 19 open · #215 of 232 all
IndependentEpoch AI ·
78.4%
78.4%
median 67.7%open leader 93.9%
Overall best: Claude Opus 5.5 Max 98.9%
64th percentile · #25 of 68 open · #122 of 214 all
Lab-reportedEpoch AI ·
52.9%
52.9%
median 61.1%open leader 86.1%
Overall best: GPT 5 (Aug 07, 2025, medium) 97.2%
38th percentile · #16 of 25 open · #39 of 58 all
IndependentEpoch AI ·
23.5%
23.5%
median 24.7%open leader 55.5%
Overall best: Claude Opus 5.5 Max 68.2%
45th percentile · #30 of 54 open · #135 of 176 all
Lab-reportedEpoch AI ·
Qwen3 235B A22B Instruct 2507 coding benchmarks
Writing, editing, and fixing real code — measured by whether the resulting program actually runs and passes tests.
59.6%
59.6%
median 45.1%open leader 74.2%
Overall best: GPT 5 (Aug 07, 2025, high) 88.0%
85th percentile · #4 of 18 open · #28 of 69 all
IndependentEpoch AI ·
38.7%
38.7%
median 39.5%open leader 82.6%
Overall best: GPT 6 Astra Promax 93.6%
44th percentile · #26 of 46 open · #115 of 162 all
IndependentEpoch AI ·
Qwen3 235B A22B Instruct 2507 knowledge benchmarks
Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.
Qwen3 235B A22B Instruct 2507 instruction following benchmarks
How precisely a model obeys explicit, verifiable instructions — format, length, and content constraints — and, more broadly, how much people prefer its responses head-to-head in blind human voting.
1422.1
1422.1
median 1321.5open leader 1487.1
Overall best: Gemini 4 Argon (High) 1523.9
83rd percentile · #32 of 187 open · #124 of 405 all
ArenaArena ·
Score vs VRAM in the ≤192 GB tier
- Qwen3 235B A22B Instruct 2507
- Other models
- Best Score for its VRAM
#37 of 78 that fit ≤192 GB
Each dot is a model at the best quant that fits ≤192 GB. The line joins the models with the best Score for their VRAM; a dot below it is beaten by a model that needs no more memory.
Full ≤192 GB ranking →Qwen3 235B A22B Instruct 2507 vs its neighbours
Same boards for the nearest open models per llmrun Score. The highest score in each row is marked.
| Board | Qwen3 235B A22B Instruct 2507this model | Qwen3.8 27Bbest in classQ4_K_M · 18 GB | GLM 4.5nearest by ScoreQ4_K_M · 218 GB | Qwen3 235B A22Bnearest by ScoreQ4_K_M · 143 GB | Mistral Small 4 119B 2603nearest by ScoreQ4_K_M · 82 GB |
|---|---|---|---|---|---|
| llmrun Score | 98.5 | 122.1 | 100.9 | 99.6 | 96.4 |
| ARC-AGI-2 | 1.3% | 42.4% | — | — | — |
| ARC-AGI | 11.0% | 87.5% | — | — | — |
| DTBench | 78.4% | 88.0% | — | 75.7% | 70.9% |
| Fiction.LiveBench | 52.9% | — | 58.3% | 67.7% | — |
| LMCA | 23.5% | 41.4% | — | 25.0% | 20.6% |
| Aider Polyglot | 59.6% | — | — | 59.6% | — |
| WeirdML | 38.7% | — | 40.6% | 37.3% | — |
| MMLU-Pro | 83.0% | — | 84.6% | 68.2% | — |
| LMArena Text | 1422.1 | 1437.8 | 1410.8 | 1402.0 | — |
| Compare head to head | Compare | Compare | Compare | Compare |
Scores aggregated from public benchmark sources (Epoch AI: 7 boards, Arena: 1 board, TIGER-Lab: 1 board) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.