Mistral Large 4 vs Qwen3.7 Max
Mistral Large 4 leads Qwen3.7 Max on coding, 56.4 to 54.1 on the Vibe Coding Index, at about the same output price ($4.18 vs $4.425 per million). Updated October 22, 2026; 35 benchmarks have a result for both.
Mistral Large 4 or Qwen3.7 Max: which to pick
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 54.1 for Qwen3.7 Max.
Pick Qwen3.7 Max for work measured by LMArena WebDev: HTML or Epoch Capabilities Index, where it leads.
- Shared results
- 35
- Mistral Large 4 only
- 46
- Qwen3.7 Max only
- 24
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
Mistral Large 4
Mistral Large 4 scores 56.4 against 54.1.
5 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 29.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Max has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.7 Max has a GPQA Diamond result, 90.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.7 Max has a MMLU Pro result, 89.3%.
Directional only
Web design
Design Arena: websites
Qwen3.7 Max
Qwen3.7 Max leads, 1274 against 1257.
Same board, both measured
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large 4
Mistral Large 4 $0.0034, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.7 Max has the number, $4.69.
Directional only
At a glance
- Coding index
- Mistral Large 4 56.4 from 5 benchmarks, Qwen3.7 Max 54.1 from 3 benchmarks.
- Widest category
- Knowledge, 18.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- SimpleQA Verified: Mistral Large 4 20.0% against Qwen3.7 Max 55.8%, 35.8 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3.7 Max $4.425 per million output tokens, 1.1x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Qwen3.7 Max 1M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Mistral Large 4 | Bars | Qwen3.7 Max | Ties |
|---|---|---|---|---|
| Coding | 6 | 1 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 3 | 1 | ||
| Reasoning | 1 | 3 | ||
| Math | 1 | 3 | ||
| Knowledge | 1 | 1 | ||
| Web design | 2 | 5 | 1 tie | |
| General | 2 | 2 | ||
| All shared boards | 17 | 17 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index61
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| LiveBench coding | 60.0% | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev | 1543 | 1515 | Mistral Large 4 |
| AA Coding Index | Not measured | 66.0 | Only Qwen3.7 Max measured |
| LiveCodeBench (Vals AI) | Not measured | 87.1% | Only Qwen3.7 Max measured |
| SWE-bench Verified (Vals AI) | Not measured | 68.8% | Only Qwen3.7 Max measured |
| Terminal-Bench 4 (Vals AI) | 27.8% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 78.4% | 47.7% | Mistral Large 4 |
| Code migration (Vals AI) | 30.6% | 13.1% | Mistral Large 4 |
| IOI (Vals AI) | 45.3% | Not measured | Only Mistral Large 4 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 61.0% | Only Qwen3.7 Max measured |
| SWE-bench Multimodal (Vals AI) | 33.1% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench 1-100 (Vals AI) | 14.3% | Not measured | Only Mistral Large 4 measured |
| SciCode | 54.2% | 49.5% | Mistral Large 4 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only Qwen3.7 Max measured |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| ALE-Bench | 1213.2 | 1189.4 | Mistral Large 4 |
| LMArena Text: coding | 1478 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: software and IT | 1467 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: React | 1559 | 1514 | Mistral Large 4 |
| LMArena WebDev: HTML | 1487 | 1512 | Qwen3.7 Max |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 29.5 | Mistral Large 4 |
| Epoch Capabilities Index | 150.0 | 154.0 | Qwen3.7 Max |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Qwen3.7 Max measured |
| Design Arena: agents building web apps | Not measured | 1208 | Only Qwen3.7 Max measured |
| Design Arena: agents building full-stack apps | Not measured | 1191 | Only Qwen3.7 Max measured |
| Design Arena: agents building mobile apps | Not measured | 1155 | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | Not measured | 1159 | Only Qwen3.7 Max measured |
| Design Arena: agents building Godot games | Not measured | 1187 | Only Qwen3.7 Max measured |
| Design Arena: agents building games | Not measured | 1161 | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | Not measured | 1108 | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | Not measured | 1171 | Only Qwen3.7 Max measured |
| LiveBench research | 28.1% | Not measured | Only Mistral Large 4 measured |
| LiveBench browser | 8.0% | Not measured | Only Mistral Large 4 measured |
| LiveBench long agentic | 11.8% | Not measured | Only Mistral Large 4 measured |
| Finance Agent (Vals AI) | 54.7% | 47.8% | Mistral Large 4 |
| Tax Agent Bench (Vals AI) | 30.4% | 15.8% | Mistral Large 4 |
| Legal Research Bench (Vals AI) | 31.7% | 25.5% | Mistral Large 4 |
| Harvey's Legal Agent Benchmark (Vals AI) | 17.5% | Not measured | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | 56.2% | 57.0% | Qwen3.7 Max |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Mistral Large 4 measured |
| τ²-Bench Telecom | Not measured | 94.7% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.2% | Only Qwen3.7 Max measured |
| LiveBench reasoning | 83.9% | Not measured | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | 12.2% | Not measured | Only Mistral Large 4 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.3% | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 40.5% | Qwen3.7 Max |
| GPQA Diamond (Epoch AI run) | 88.1% | 90.9% | Qwen3.7 Max |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | 33.0% | 26.0% | Mistral Large 4 |
| Mystery game puzzles | 17.0% | 32.0% | Qwen3.7 Max |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max measured |
| LMArena Text: hard prompts | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: expert | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | 1442 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: diagrams | 1288 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 95.6% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 58.6% | 64.6% | Qwen3.7 Max |
| FrontierMath, tier 4 | 26.8% | 34.1% | Qwen3.7 Max |
| ProofBench | 10.0% | 26.0% | Qwen3.7 Max |
| LMArena Text: math | 1469 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | 1462 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.3% | Only Qwen3.7 Max measured |
| LegalBench (Vals AI) | Not measured | 84.9% | Only Qwen3.7 Max measured |
| CorpFin (Vals AI) | Not measured | 63.7% | Only Qwen3.7 Max measured |
| TaxEval (Vals AI) | Not measured | 75.3% | Only Qwen3.7 Max measured |
| MedCode (Vals AI) | 40.7% | 38.8% | Mistral Large 4 |
| SimpleQA Verified | 20.0% | 55.8% | Qwen3.7 Max |
| LMArena Text: science | 1448 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: legal and government | 1425 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: business and finance | 1439 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1257 | 1274 | Qwen3.7 Max |
| Design Arena: UI components | 1272 | 1267 | Mistral Large 4 |
| Design Arena: game dev | 1225 | 1264 | Qwen3.7 Max |
| Design Arena: data viz | 1275 | 1275 | Tie |
| Design Arena: 3D | 1252 | 1265 | Qwen3.7 Max |
| Design Arena: all code categories | 1259 | 1275 | Qwen3.7 Max |
| Design Arena: SVG | 1232 | 1216 | Mistral Large 4 |
| Design Arena: ASCII art | 1202 | 1211 | Qwen3.7 Max |
| LiveBench design | 65.6% | Not measured | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.5% | Not measured | Only Mistral Large 4 measured |
| MedScribe (Vals AI) | 80.4% | 79.4% | Mistral Large 4 |
| IFBench | Not measured | 80.5% | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | 81.3% | 79.0% | Mistral Large 4 |
| DTBench | 88.2% | 92.3% | Qwen3.7 Max |
| LMCA | 35.8% | 44.0% | Qwen3.7 Max |
| Surface Evolver Bench | 28.1% | Not measured | Only Mistral Large 4 measured |
| Furniture assembly | 20.8% | Not measured | Only Mistral Large 4 measured |
| LMArena Text | 1431 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: instruction following | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: creative writing | 1363 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: non-English | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Chinese | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Japanese | 1415 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: French | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Spanish | 1455 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Russian | 1417 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | 1435 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: longer queries | 1428 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: writing and language | 1386 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | 1378 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: English | 1283 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: reading text | 1284 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.7 Max | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Large 4 costs less
Repository review
50K input + 3K output tokens
Mistral Large 4 costs less
Agent loop
200K input + 10K output tokens
Mistral Large 4 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Mistral Large 4 | Qwen3.7 Max |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | October 6, 2026 | May 21, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.36 | $1.475 |
| Output $/Mtok | $4.18 | $4.425 |
| Coding index | 56.4 | 54.1 |
| Independent measurements behind it | 5 | 3 |
| Cost per solved task | Not computable | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Qwen3.7 Max for coding?
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 54.1 for Qwen3.7 Max. Pick Qwen3.7 Max for work measured by LMArena WebDev: HTML or Epoch Capabilities Index, where it leads.
Which is cheaper, Mistral Large 4 or Qwen3.7 Max?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, Mistral Large 4 or Qwen3.7 Max?
Mistral Large 4, with 1.05M tokens against 1M.
How many benchmarks is the Mistral Large 4 vs Qwen3.7 Max comparison based on?
35 benchmarks have a result for both models as of October 22, 2026. Mistral Large 4's coding index rests on 5 independent benchmarks and Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.