Mistral Large 3 2512 vs Qwen3.7 Plus
Qwen3.7 Plus leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 25.2 to 9.3, at about the same output price ($1.28 vs $1.50 per million). Updated October 22, 2026; 15 benchmarks have a result for both.
Mistral Large 3 2512 or Qwen3.7 Plus: which to pick
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 15
- Mistral Large 3 2512 only
- 13
- Qwen3.7 Plus only
- 60
- Like-for-like categories
- 6 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 Plus has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.7 Plus
Qwen3.7 Plus leads, 25.2 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.7 Plus
Qwen3.7 Plus leads, 17.5 against 1.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Mistral Large 3 2512 has a GPQA Diamond result, 68.4%.
Directional only
Math
AIME
No call
Only Mistral Large 3 2512 has a AIME result, 42.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large 3 2512 has a MMLU Pro result, 79.8%.
Directional only
Web design
Design Arena: websites
Qwen3.7 Plus
Qwen3.7 Plus leads, 1269 against 1162.
Same board, both measured
Long documents
Listed context window
Qwen3.7 Plus
Qwen3.7 Plus takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Plus
Mistral Large 3 2512 $0.0013, Qwen3.7 Plus $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Large 3 2512 has the number, $0.77.
Directional only
At a glance
- Coding index
- Mistral Large 3 2512 not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
- Widest category
- Coding, 35.8 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: Mistral Large 3 2512 20.1 against Qwen3.7 Plus 55.9, 35.8 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Qwen3.7 Plus $1.28 per million output tokens, 1.2x apart.
- Context window
- Mistral Large 3 2512 takes 262K tokens, Qwen3.7 Plus 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 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Knowledge | 0 | 1 | ||
| Web design | 0 | 8 | ||
| General | 0 | 3 | ||
| All shared boards | 0 | 15 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Coding Index | 20.1 | 55.9 | Qwen3.7 Plus |
| LiveCodeBench (Vals AI) | 55.3% | Not measured | Only Mistral Large 3 2512 measured |
| SWE-bench Verified (Vals AI) | 41.4% | Not measured | Only Mistral Large 3 2512 measured |
| Vibe Code Bench (Vals AI) | Not measured | 46.4% | Only Qwen3.7 Plus measured |
| Code migration (Vals AI) | Not measured | 12.9% | Only Qwen3.7 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 52.8% | Only Qwen3.7 Plus measured |
| SkillsBench (Vals AI) | Not measured | 54.3% | Only Qwen3.7 Plus measured |
| SciCode | Not measured | 46.1% | Only Qwen3.7 Plus measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 47.0% | Only Qwen3.7 Plus measured |
| FrontierCode | Not measured | 10.2% | Only Qwen3.7 Plus measured |
| ALE-Bench | 264.7 | Not measured | Only Mistral Large 3 2512 measured |
| LMArena Text: coding | Not measured | 1473 | Only Qwen3.7 Plus measured |
| LMArena Text: software and IT | Not measured | 1473 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | 25.2 | Qwen3.7 Plus |
| Epoch Capabilities Index | Not measured | 147.0 | Only Qwen3.7 Plus measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 17.5 | Qwen3.7 Plus |
| Finance Agent (Vals AI) | Not measured | 38.2% | Only Qwen3.7 Plus measured |
| Tax Agent Bench (Vals AI) | Not measured | 10.5% | Only Qwen3.7 Plus measured |
| Legal Research Bench (Vals AI) | Not measured | 16.4% | Only Qwen3.7 Plus measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 49.3% | Only Qwen3.7 Plus measured |
| τ²-Bench Telecom | Not measured | 93.0% | Only Qwen3.7 Plus measured |
| OSWorld 2.0 | Not measured | 2.8% | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 68.4% | Not measured | Only Mistral Large 3 2512 measured |
| MMMU Pro (Vals AI) | 66.2% | Not measured | Only Mistral Large 3 2512 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 90.0% | Only Qwen3.7 Plus measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 35.6% | Only Qwen3.7 Plus measured |
| GPQA Diamond (Epoch AI run) | Not measured | 87.9% | Only Qwen3.7 Plus measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Text: expert | Not measured | 1466 | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Vision: diagrams | Not measured | 1292 | Only Qwen3.7 Plus measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | 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 | 93.3% | Only Qwen3.7 Plus measured |
| FrontierMath, tiers 1 to 3 | Not measured | 34.4% | Only Qwen3.7 Plus measured |
| LMArena Text: math | Not measured | 1467 | Only Qwen3.7 Plus measured |
| LMArena Text: mathematical work | Not measured | 1470 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 79.8% | Not measured | Only Mistral Large 3 2512 measured |
| LegalBench (Vals AI) | 79.1% | Not measured | Only Mistral Large 3 2512 measured |
| CaseLaw (Vals AI) | 61.4% | Not measured | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | 61.0% | Not measured | Only Mistral Large 3 2512 measured |
| TaxEval (Vals AI) | 73.1% | Not measured | Only Mistral Large 3 2512 measured |
| MortgageTax (Vals AI) | 52.1% | 66.2% | Qwen3.7 Plus |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| LMArena Text: science | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: legal and government | Not measured | 1451 | Only Qwen3.7 Plus measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1269 | Qwen3.7 Plus |
| Design Arena: UI components | 1099 | 1258 | Qwen3.7 Plus |
| Design Arena: game dev | 1080 | 1261 | Qwen3.7 Plus |
| Design Arena: data viz | 1136 | 1276 | Qwen3.7 Plus |
| Design Arena: 3D | 1099 | 1238 | Qwen3.7 Plus |
| Design Arena: all code categories | 1141 | 1269 | Qwen3.7 Plus |
| Design Arena: SVG | 992 | 1208 | Qwen3.7 Plus |
| Design Arena: ASCII art | 1069 | 1143 | Qwen3.7 Plus |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 24.6% | 39.3% | Qwen3.7 Plus |
| Vals Multimodal Index | Not measured | 53.9% | Only Qwen3.7 Plus measured |
| IFBench | Not measured | 78.0% | Only Qwen3.7 Plus measured |
| Long context reasoning (AA-LCR) | Not measured | 73.0% | Only Qwen3.7 Plus measured |
| DTBench | 65.1% | 84.0% | Qwen3.7 Plus |
| LMCA | 16.7% | 37.6% | Qwen3.7 Plus |
| LMArena Text | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: instruction following | Not measured | 1439 | Only Qwen3.7 Plus measured |
| LMArena Text: creative writing | Not measured | 1438 | Only Qwen3.7 Plus measured |
| LMArena Vision | Not measured | 1278 | Only Qwen3.7 Plus measured |
| LMArena Text: English | Not measured | 1458 | Only Qwen3.7 Plus measured |
| LMArena Text: non-English | Not measured | 1445 | Only Qwen3.7 Plus measured |
| LMArena Text: Chinese | Not measured | 1509 | Only Qwen3.7 Plus measured |
| LMArena Text: German | Not measured | 1471 | Only Qwen3.7 Plus measured |
| LMArena Text: Japanese | Not measured | 1412 | Only Qwen3.7 Plus measured |
| LMArena Text: Korean | Not measured | 1413 | Only Qwen3.7 Plus measured |
| LMArena Text: French | Not measured | 1472 | Only Qwen3.7 Plus measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Russian | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Polish | Not measured | 1449 | Only Qwen3.7 Plus measured |
| LMArena Text: multi-turn | Not measured | 1459 | Only Qwen3.7 Plus measured |
| LMArena Text: longer queries | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: writing and language | Not measured | 1437 | Only Qwen3.7 Plus measured |
| LMArena Text: entertainment and media | Not measured | 1422 | Only Qwen3.7 Plus measured |
| LMArena Vision: English | Not measured | 1280 | Only Qwen3.7 Plus measured |
| LMArena Vision: Chinese | Not measured | 1332 | Only Qwen3.7 Plus measured |
| LMArena Vision: reading text | Not measured | 1288 | Only Qwen3.7 Plus measured |
| LMArena Vision: humor | Not measured | 1261 | Only Qwen3.7 Plus measured |
| LMArena Vision: creative writing | Not measured | 1258 | Only Qwen3.7 Plus measured |
| LMArena Document | Not measured | 1444 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.7 Plus | 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
Qwen3.7 Plus costs less
Repository review
50K input + 3K output tokens
Qwen3.7 Plus costs less
Agent loop
200K input + 10K output tokens
Qwen3.7 Plus 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 Plus |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | December 1, 2025 | June 3, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.50 | $0.32 |
| Output $/Mtok | $1.50 | $1.28 |
| Coding index | Not benchmarked | 33.2 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.77 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Qwen3.7 Plus for coding?
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Mistral Large 3 2512 or Qwen3.7 Plus?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for Mistral Large 3 2512 only.
Which has the bigger context window, Mistral Large 3 2512 or Qwen3.7 Plus?
Qwen3.7 Plus, with 1M tokens against 262K.
How many benchmarks is the Mistral Large 3 2512 vs Qwen3.7 Plus comparison based on?
15 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 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.