Model comparison
Pixtral Large vs Qwen3.7 Max
Qwen3.7 Max is the stronger model overall, scoring 51.4 to 31.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- The widest gap is in writing & preference, where Qwen3.7 Max leads 65.2 to 32.9.
- Pixtral Large is cheaper at $2 / $6 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Qwen3.7 Max accepts more context: 1M tokens versus 128K.
- Pixtral Large has downloadable open weights; the other is API-only.
Side by side
| Pixtral Large | Qwen3.7 Max | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.7 | 51.4 |
| Released | 2024-11-01 | 2026-05-19 |
| Weights | Open | Proprietary |
| Context window | 128K | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $2.50 |
| Output $ / M tokens | $6 | $7.50 |
| Results tracked | 3 | 33 |
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Category by category
Coding Not comparable
Pixtral Large: —, Qwen3.7 Max: 50.2 (#43)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| SWE-bench Verified | — | 77.3% |
| LMArena WebDev | — | 1515 |
| SciCode | — | 48.8% |
| LMArena Coding | — | 1498 |
| ALE-Bench | — | 1,189 |
Agentic & Tool Use Not comparable
Pixtral Large: —, Qwen3.7 Max: 21.8 (#129)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| GBAEval | — | 0.4% |
Reasoning Qwen3.7 Max leads
Pixtral Large: 20.9 (#208), Qwen3.7 Max: 48.4 (#36)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| SimpleBench | — | 70.4% |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 13.4% |
| Chess Puzzles | — | 19% |
| EnigmaEval | 0.8% | — |
| EBR-Bench | — | 9.5% |
| LMArena Hard Prompts | — | 1483 |
| Mystery Game Puzzles | — | 32% |
| DTBench | — | 92.3% |
| LMCA | — | 44% |
| Epoch Capabilities Index | — | 153.74 |
Math Not comparable
Pixtral Large: —, Qwen3.7 Max: 62.3 (#26)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 64.6% |
| FrontierMath Tier 4 | — | 34.1% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| ProofBench | — | 26% |
| LMArena Math | — | 1488 |
Knowledge Not comparable
Pixtral Large: —, Qwen3.7 Max: 61.7 (#24)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 55.8% |
| LMArena Expert | — | 1488 |
Multimodal Not comparable
Pixtral Large: 30.0 (#105), Qwen3.7 Max: —
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| LMArena Vision | 1089 | — |
Multilingual Not comparable
Pixtral Large: —, Qwen3.7 Max: 57.1 (#13)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | — | 1475 |
| LMArena Chinese | — | 1533 |
| LMArena Russian | — | 1482 |
Instruction Following Not comparable
Pixtral Large: —, Qwen3.7 Max: 76.9 (#34)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | — | 1460 |
Long Context Not comparable
Pixtral Large: —, Qwen3.7 Max: 45.4 (#34)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | — | 1484 |
Writing & Preference Qwen3.7 Max leads
Pixtral Large: 32.9 (#273), Qwen3.7 Max: 65.2 (#52)
| Benchmark | Pixtral Large | Qwen3.7 Max |
|---|---|---|
| LMArena Text | — | 1476 |
| LMArena Creative Writing | — | 1450 |
| EQ-Bench Creative Writing | 988 | — |
| EQ-Bench 4 | — | 1110 |
| LMArena Multi-Turn | — | 1482 |
Frequently asked questions
Is Pixtral Large better than Qwen3.7 Max?
Qwen3.7 Max is the stronger model overall, scoring 51.4 to 31.7 on the Noometry Index.
Which is cheaper, Pixtral Large or Qwen3.7 Max?
Pixtral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.
Which has the bigger context window?
Qwen3.7 Max does, with 1M tokens against 128K.
How many benchmarks do Pixtral Large and Qwen3.7 Max share?
0 benchmarks have published results for both models. Pixtral Large has 3 scored results on Noometry and Qwen3.7 Max has 33.