Mistral Large 3 2512 vs Qwen3.5 397B A17B
Qwen3.5 397B A17B leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 21.4 to 9.3, and Mistral Large 3 2512 costs 1.6x less per output token ($1.50 vs $2.34 per million). Updated October 22, 2026; 11 benchmarks have a result for both.
Mistral Large 3 2512 or Qwen3.5 397B A17B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for output tokens 1.6x cheaper ($1.50 vs $2.34 per million) and work measured by ALE-Bench or AA Intelligence Index, where it leads.
- Shared results
- 11
- Mistral Large 3 2512 only
- 17
- Qwen3.5 397B A17B only
- 54
- Like-for-like categories
- 4 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 21.4 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Large 3 2512 has a AA Agentic Index result, 1.0.
Directional only
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
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 1190 against 1162.
Same board, both measured
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large 3 2512
Mistral Large 3 2512 $0.0013, Qwen3.5 397B A17B $0.0016 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, Qwen3.5 397B A17B not benchmarked.
- Widest category
- General, 21.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- DTBench: Mistral Large 3 2512 65.1% against Qwen3.5 397B A17B 87.5%, 22.4 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.6x apart.
- Context window
- Both take 262K tokens.
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 | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Web design | 0 | 7 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Mistral Large 3 2512 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1400 | Only Qwen3.5 397B A17B measured |
| AA Coding Index | 20.1 | Not measured | Only Mistral Large 3 2512 measured |
| 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 |
| SciCode | Not measured | 44.8% | Only Qwen3.5 397B A17B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 40.9% | Only Qwen3.5 397B A17B measured |
| ALE-Bench | 264.7 | 621.9 | Qwen3.5 397B A17B |
| LMArena Text: coding | Not measured | 1464 | Only Qwen3.5 397B A17B measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: React | Not measured | 1388 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: HTML | Not measured | 1410 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | 21.4 | Qwen3.5 397B A17B |
| Epoch Capabilities Index | Not measured | 146.8 | Only Qwen3.5 397B A17B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Mistral Large 3 2512 measured |
| τ²-Bench Telecom | Not measured | 95.6% | Only Qwen3.5 397B A17B measured |
| APEX-Agents | Not measured | 24.9% | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.5 397B A17B | 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 | 89.3% | Only Qwen3.5 397B A17B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 29.0% | Only Qwen3.5 397B A17B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 86.4% | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | Not measured | 1448 | Only Qwen3.5 397B A17B measured |
| LMArena Text: expert | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts in English | Not measured | 1450 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B | 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 | 88.9% | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 31.2% | Only Qwen3.5 397B A17B measured |
| LMArena Text: math | Not measured | 1453 | Only Qwen3.5 397B A17B measured |
| LMArena Text: mathematical work | Not measured | 1454 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.5 397B A17B | 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% | Not measured | Only Mistral Large 3 2512 measured |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| LMArena Text: science | Not measured | 1457 | Only Qwen3.5 397B A17B measured |
| LMArena Text: medicine and healthcare | Not measured | 1455 | Only Qwen3.5 397B A17B measured |
| LMArena Text: legal and government | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Mistral Large 3 2512 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1190 | Qwen3.5 397B A17B |
| Design Arena: UI components | 1099 | 1161 | Qwen3.5 397B A17B |
| Design Arena: game dev | 1080 | 1140 | Qwen3.5 397B A17B |
| Design Arena: data viz | 1137 | 1175 | Qwen3.5 397B A17B |
| Design Arena: 3D | 1099 | 1160 | Qwen3.5 397B A17B |
| Design Arena: all code categories | 1141 | 1179 | Qwen3.5 397B A17B |
| Design Arena: SVG | 992 | 1139 | Qwen3.5 397B A17B |
| Design Arena: ASCII art | 1069 | Not measured | Only Mistral Large 3 2512 measured |
| 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 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 24.6% | Not measured | Only Mistral Large 3 2512 measured |
| IFBench | Not measured | 78.8% | Only Qwen3.5 397B A17B measured |
| Long context reasoning (AA-LCR) | Not measured | 77.3% | Only Qwen3.5 397B A17B measured |
| DTBench | 65.1% | 87.5% | Qwen3.5 397B A17B |
| LMCA | 16.7% | 37.9% | Qwen3.5 397B A17B |
| LMArena Text | Not measured | 1437 | Only Qwen3.5 397B A17B measured |
| LMArena Text: instruction following | Not measured | 1424 | Only Qwen3.5 397B A17B measured |
| LMArena Text: creative writing | Not measured | 1402 | Only Qwen3.5 397B A17B measured |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | Not measured | 1443 | Only Qwen3.5 397B A17B measured |
| LMArena Text: non-English | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Chinese | Not measured | 1498 | Only Qwen3.5 397B A17B measured |
| LMArena Text: German | Not measured | 1445 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Japanese | Not measured | 1429 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.5 397B A17B measured |
| LMArena Text: French | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Spanish | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Russian | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Polish | Not measured | 1447 | Only Qwen3.5 397B A17B measured |
| LMArena Text: multi-turn | Not measured | 1446 | Only Qwen3.5 397B A17B measured |
| LMArena Text: longer queries | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: writing and language | Not measured | 1415 | Only Qwen3.5 397B A17B measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B | 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
Qwen3.5 397B A17B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | December 1, 2025 | February 16, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.50 | $0.39 |
| Output $/Mtok | $1.50 | $2.34 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.77 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Qwen3.5 397B A17B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for output tokens 1.6x cheaper ($1.50 vs $2.34 per million) and work measured by ALE-Bench or AA Intelligence Index, where it leads.
Which is cheaper, Mistral Large 3 2512 or Qwen3.5 397B A17B?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for Mistral Large 3 2512 only.
Which has the bigger context window, Mistral Large 3 2512 or Qwen3.5 397B A17B?
Neither: both take 262K tokens.
How many benchmarks is the Mistral Large 3 2512 vs Qwen3.5 397B A17B comparison based on?
11 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 Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.