Mistral Large 3 2512 vs Qwen3.7 Max
Qwen3.7 Max leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 29.5 to 9.3, and Mistral Large 3 2512 costs 2.9x less per output token ($1.50 vs $4.425 per million). Updated October 22, 2026; 21 benchmarks have a result for both.
Mistral Large 3 2512 or Qwen3.7 Max: which to pick
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for output tokens 2.9x cheaper ($1.50 vs $4.425 per million) and a lower cost per solved task ($0.77 against $4.69).
- Shared results
- 21
- Mistral Large 3 2512 only
- 7
- Qwen3.7 Max only
- 38
- Like-for-like categories
- 7 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
No call
Only Qwen3.7 Max has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.7 Max
Qwen3.7 Max leads, 29.5 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.7 Max
Qwen3.7 Max leads, 22.5 against 1.0.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.7 Max
Qwen3.7 Max leads, 90.2% against 68.4%.
Same board, both measured
Math
AIME
No call
Only Mistral Large 3 2512 has a AIME result, 42.9%.
Directional only
Knowledge
MMLU Pro
Qwen3.7 Max
Qwen3.7 Max leads, 89.3% against 79.8%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.7 Max
Qwen3.7 Max leads, 1274 against 1162.
Same board, both measured
Long documents
Listed context window
Qwen3.7 Max
Qwen3.7 Max takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large 3 2512
Mistral Large 3 2512 $0.0013, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Mistral Large 3 2512
Mistral Large 3 2512 $0.77, Qwen3.7 Max $4.69.
Published attempt cost and pass rate
At a glance
- Coding index
- Mistral Large 3 2512 not benchmarked, Qwen3.7 Max 54.1 from 3 benchmarks.
- Widest category
- Coding, 34.0 points apart on average over 4 shared benchmarks.
- Widest single gap
- AA Coding Index: Mistral Large 3 2512 20.1 against Qwen3.7 Max 66.0, 45.9 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Qwen3.7 Max $4.425 per million output tokens, 2.9x apart.
- Context window
- Mistral Large 3 2512 takes 262K 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 3 2512 | Bars | Qwen3.7 Max | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 8 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 21 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1515 | Only Qwen3.7 Max measured |
| AA Coding Index | 20.1 | 66.0 | Qwen3.7 Max |
| LiveCodeBench (Vals AI) | 55.3% | 87.1% | Qwen3.7 Max |
| SWE-bench Verified (Vals AI) | 41.4% | 68.8% | Qwen3.7 Max |
| Vibe Code Bench (Vals AI) | Not measured | 47.7% | Only Qwen3.7 Max measured |
| Code migration (Vals AI) | Not measured | 13.1% | Only Qwen3.7 Max measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 61.0% | Only Qwen3.7 Max measured |
| SciCode | Not measured | 49.5% | Only Qwen3.7 Max measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only Qwen3.7 Max measured |
| ALE-Bench | 264.7 | 1189.4 | Qwen3.7 Max |
| LMArena WebDev: React | Not measured | 1514 | Only Qwen3.7 Max measured |
| LMArena WebDev: HTML | Not measured | 1512 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | 29.5 | Qwen3.7 Max |
| Epoch Capabilities Index | Not measured | 154.0 | Only Qwen3.7 Max measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 22.5 | Qwen3.7 Max |
| 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 |
| Finance Agent (Vals AI) | Not measured | 47.8% | Only Qwen3.7 Max measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.8% | Only Qwen3.7 Max measured |
| Legal Research Bench (Vals AI) | Not measured | 25.5% | Only Qwen3.7 Max measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.0% | Only Qwen3.7 Max measured |
| τ²-Bench Telecom | Not measured | 94.7% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | 68.4% | 90.2% | Qwen3.7 Max |
| MMMU Pro (Vals AI) | 66.2% | Not measured | Only Mistral Large 3 2512 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.3% | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 40.5% | Only Qwen3.7 Max measured |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only Qwen3.7 Max measured |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | Not measured | 26.0% | Only Qwen3.7 Max measured |
| Mystery game puzzles | Not measured | 32.0% | Only Qwen3.7 Max measured |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AIME | 42.9% | Not measured | Only Mistral Large 3 2512 measured |
| MGSM (Vals AI) | 85.4% | Not measured | Only Mistral Large 3 2512 measured |
| OTIS Mock AIME | Not measured | 95.6% | Only Qwen3.7 Max measured |
| FrontierMath, tiers 1 to 3 | Not measured | 64.6% | Only Qwen3.7 Max measured |
| FrontierMath, tier 4 | Not measured | 34.1% | Only Qwen3.7 Max measured |
| ProofBench | Not measured | 26.0% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | 79.8% | 89.3% | Qwen3.7 Max |
| LegalBench (Vals AI) | 79.1% | 84.9% | Qwen3.7 Max |
| CaseLaw (Vals AI) | 61.4% | Not measured | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | 61.0% | 63.7% | Qwen3.7 Max |
| TaxEval (Vals AI) | 73.1% | 75.3% | Qwen3.7 Max |
| MortgageTax (Vals AI) | 52.1% | Not measured | Only Mistral Large 3 2512 measured |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| MedCode (Vals AI) | Not measured | 38.8% | Only Qwen3.7 Max measured |
| SimpleQA Verified | Not measured | 55.8% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 9 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1274 | Qwen3.7 Max |
| Design Arena: UI components | 1099 | 1267 | Qwen3.7 Max |
| Design Arena: game dev | 1080 | 1264 | Qwen3.7 Max |
| Design Arena: data viz | 1136 | 1275 | Qwen3.7 Max |
| Design Arena: 3D | 1099 | 1265 | Qwen3.7 Max |
| Design Arena: all code categories | 1141 | 1275 | Qwen3.7 Max |
| Design Arena: SVG | 992 | 1216 | Qwen3.7 Max |
| Design Arena: ASCII art | 1069 | 1211 | Qwen3.7 Max |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Max | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 24.6% | Not measured | Only Mistral Large 3 2512 measured |
| MedScribe (Vals AI) | Not measured | 79.4% | Only Qwen3.7 Max measured |
| IFBench | Not measured | 80.5% | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | Not measured | 79.0% | Only Qwen3.7 Max measured |
| DTBench | 65.1% | 92.3% | Qwen3.7 Max |
| LMCA | 16.7% | 44.0% | Qwen3.7 Max |
| Neither model has a result on the other 40 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 3 2512 | 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 3 2512 costs less
Repository review
50K input + 3K output tokens
Mistral Large 3 2512 costs less
Agent loop
200K input + 10K output tokens
Mistral Large 3 2512 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 3 2512 | Qwen3.7 Max |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | December 1, 2025 | May 21, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.50 | $1.475 |
| Output $/Mtok | $1.50 | $4.425 |
| Coding index | Not benchmarked | 54.1 |
| Independent measurements behind it | 1 | 3 |
| Cost per solved task | $0.77 | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Qwen3.7 Max for coding?
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for output tokens 2.9x cheaper ($1.50 vs $4.425 per million) and a lower cost per solved task ($0.77 against $4.69).
Which is cheaper, Mistral Large 3 2512 or Qwen3.7 Max?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Per solved SWE-bench Verified task, Mistral Large 3 2512 costs $0.77 and Qwen3.7 Max $4.69.
Which has the bigger context window, Mistral Large 3 2512 or Qwen3.7 Max?
Qwen3.7 Max, with 1M tokens against 262K.
How many benchmarks is the Mistral Large 3 2512 vs Qwen3.7 Max comparison based on?
21 benchmarks have a result for both models as of October 22, 2026. Mistral Large 3 2512's coding index rests on 1 independent benchmark and Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.