Model comparison
Mistral Large 3 vs Qwen3.7 Max
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 39.1 on the Noometry Index. Mistral Large 3 costs 10× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 14 benchmarks with published results for both. Mistral Large 3 scores higher in 0 categories and Qwen3.7 Max in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.7 Max leads 49.2 to 15.2.
- The biggest single-benchmark swing is NYT Connections (extended): 7.5% for Mistral Large 3 and 85.1% for Qwen3.7 Max.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Qwen3.7 Max accepts more context: 1M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| Mistral Large 3 | Qwen3.7 Max | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 39.1 | 51.5 |
| Released | 2025-12-02 | 2026-05-19 |
| Weights | Open | Proprietary |
| Context window | 262K | 1M |
| Max output | 8K | 131K |
| Input $ / M tokens | $0.25 | $2.50 |
| Output $ / M tokens | $0.75 | $7.50 |
| Results tracked | 24 | 33 |
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Category by category
Coding Qwen3.7 Max leads
Mistral Large 3: 34.4 (#237), Qwen3.7 Max: 50.4 (#45)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena WebDev | 1230 | 1515 |
| LMArena Coding | 1448 | 1498 |
| SWE-bench Verified | — | 77.3% |
| SciCode | — | 48.8% |
| ALE-Bench | — | 1,189 |
Agentic & Tool Use Not comparable
Mistral Large 3: —, Qwen3.7 Max: 22.1 (#135)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| GBAEval | — | 0.4% |
Reasoning Qwen3.7 Max leads
Mistral Large 3: 15.2 (#319), Qwen3.7 Max: 49.2 (#38)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| NYT Connections (extended) | 7.5% | 85.1% |
| LMArena Hard Prompts | 1429 | 1483 |
| SimpleBench | — | 70.4% |
| Kagi LLM Benchmark | 50.9% | — |
| CritPt | — | 13.4% |
| Chess Puzzles | — | 19% |
| Thematic Generalization | 23% | — |
| EBR-Bench | — | 9.5% |
| Mystery Game Puzzles | — | 32% |
| DTBench | — | 92.3% |
| LMCA | — | 44% |
| Epoch Capabilities Index | — | 153.68 |
Math Qwen3.7 Max leads
Mistral Large 3: 38.7 (#129), Qwen3.7 Max: 62.4 (#32)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena Math | 1414 | 1490 |
| FrontierMath (Tiers 1-3) | — | 64.6% |
| FrontierMath Tier 4 | — | 34.1% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| ProofBench | — | 26% |
Knowledge Qwen3.7 Max leads
Mistral Large 3: 36.0 (#177), Qwen3.7 Max: 61.6 (#28)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena Expert | 1421 | 1488 |
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 55.8% |
| Vectara Hallucination Rate | 14.5% | — |
Multimodal Not comparable
Mistral Large 3: 38.2 (#66), Qwen3.7 Max: —
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena Vision | 1221 | — |
Multilingual Qwen3.7 Max leads
Mistral Large 3: 52.5 (#84), Qwen3.7 Max: 56.9 (#15)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1413 | 1474 |
| LMArena Chinese | 1447 | 1530 |
| LMArena Russian | 1411 | 1484 |
| LMArena French | 1455 | — |
| LMArena German | 1437 | — |
| LMArena Japanese | 1394 | — |
| LMArena Korean | 1384 | — |
| LMArena Spanish | 1440 | — |
Instruction Following Qwen3.7 Max leads
Mistral Large 3: 74.0 (#108), Qwen3.7 Max: 76.7 (#38)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1403 | 1460 |
Long Context Qwen3.7 Max leads
Mistral Large 3: 43.1 (#105), Qwen3.7 Max: 45.4 (#40)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1413 | 1482 |
Writing & Preference Qwen3.7 Max leads
Mistral Large 3: 60.0 (#101), Qwen3.7 Max: 65.0 (#54)
| Benchmark | Mistral Large 3 | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1428 | 1476 |
| LMArena Creative Writing | 1386 | 1449 |
| LMArena Multi-Turn | 1429 | 1481 |
| EQ-Bench Creative Writing | 1412 | — |
| EQ-Bench 4 | — | 1110 |
Frequently asked questions
Is Mistral Large 3 better than Qwen3.7 Max?
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 39.1 on the Noometry Index. Mistral Large 3 costs 10× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Which is cheaper, Mistral Large 3 or Qwen3.7 Max?
Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.
Is Mistral Large 3 or Qwen3.7 Max better for coding?
Qwen3.7 Max scores higher on coding benchmarks: 50.4 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Qwen3.7 Max does, with 1M tokens against 262K.
How many benchmarks do Mistral Large 3 and Qwen3.7 Max share?
14 benchmarks have published results for both models. Mistral Large 3 has 24 scored results on Noometry and Qwen3.7 Max has 33.