Mistral Large 4 vs Qwen3 32B
Updated October 21, 2026. 31 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 31 shared
Decision reading
Pick Mistral Large 4 for coding: it scores 55.3 on the Vibe Coding Index against 40.0 for Qwen3 32B.
Pick Qwen3 32B when output tokens cost 14.9x less.
Model AMistral Large 4Mistral AI55.3/1002 independent benchmarksNo cost per solved taskModel BQwen3 32BQwen40.0/1001 independent benchmarkNo cost per solved task
- Shared results
- 31
- Mistral Large 4 only
- 50
- Qwen3 32B only
- 11
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Mistral Large 4
Mistral Large 4 scores 55.3 against 40.0.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 7.3.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Large 4 has a Design Arena: websites result, 1258.
Directional only
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 32B
Mistral Large 4 $0.0034, Qwen3 32B $0.0002 per turn.
List prices
At a glance
- Coding index
- Mistral Large 4 55.3 from 2 benchmarks, Qwen3 32B 40.0 from 1 benchmark.
- Widest category
- Intelligence, 22.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Mistral Large 4 81.3% against Qwen3 32B 0.0%, 81.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3 32B $0.28 per million output tokens, 14.9x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Qwen3 32B 131K.
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 32B | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 14 | 0 | ||
| All shared boards | 31 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index30
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 40.0% | Only Qwen3 32B measured |
| LiveBench coding | 60.0% | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev | 1543 | Not measured | Only Mistral Large 4 measured |
| Terminal-Bench 4 (Vals AI) | 27.8% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 78.4% | Not measured | Only Mistral Large 4 measured |
| Code migration (Vals AI) | 30.6% | Not measured | Only Mistral Large 4 measured |
| IOI (Vals AI) | 45.3% | Not measured | Only Mistral Large 4 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 54.6% | Only Qwen3 32B measured |
| SciCode | 54.2% | 36.0% | Mistral Large 4 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 3.0% | Only Qwen3 32B measured |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| ALE-Bench | 1213.2 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: coding | 1478 | 1357 | Mistral Large 4 |
| LMArena Text: software and IT | 1467 | 1366 | Mistral Large 4 |
| LMArena WebDev: React | 1559 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | 1487 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 7.3 | Mistral Large 4 |
| Epoch Capabilities Index | 150.0 | 138.4 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| 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% | Not measured | Only Mistral Large 4 measured |
| Tax Agent Bench (Vals AI) | 30.4% | Not measured | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | 31.7% | Not measured | Only Mistral Large 4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 17.5% | Not measured | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | 56.2% | Not measured | Only Mistral Large 4 measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Mistral Large 4 measured |
| τ²-Bench Telecom | Not measured | 29.8% | Only Qwen3 32B measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| 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 | 66.8% | Only Qwen3 32B measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 7.4% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | 88.1% | 65.7% | Mistral Large 4 |
| Chess puzzles | 33.0% | Not measured | Only Mistral Large 4 measured |
| Mystery game puzzles | 17.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | 1444 | 1334 | Mistral Large 4 |
| LMArena Text: expert | 1444 | 1362 | Mistral Large 4 |
| LMArena Text: hard prompts in English | 1442 | 1350 | Mistral Large 4 |
| LMArena Vision: diagrams | 1288 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 73.0 | Only Qwen3 32B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.0% | Only Qwen3 32B measured |
| OTIS Mock AIME | 98.3% | 66.9% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 58.6% | Not measured | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only Mistral Large 4 measured |
| ProofBench | 10.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: math | 1469 | 1399 | Mistral Large 4 |
| LMArena Text: mathematical work | 1462 | 1420 | Mistral Large 4 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.7% | Not measured | Only Mistral Large 4 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 79.8% | Only Qwen3 32B measured |
| SimpleQA Verified | 20.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: science | 1448 | 1372 | Mistral Large 4 |
| LMArena Text: medicine and healthcare | 1433 | 1368 | Mistral Large 4 |
| LMArena Text: legal and government | 1425 | 1324 | Mistral Large 4 |
| LMArena Text: business and finance | 1439 | 1318 | Mistral Large 4 |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| Design Arena: websites | 1258 | Not measured | Only Mistral Large 4 measured |
| Design Arena: UI components | 1275 | Not measured | Only Mistral Large 4 measured |
| Design Arena: game dev | 1226 | Not measured | Only Mistral Large 4 measured |
| Design Arena: data viz | 1274 | Not measured | Only Mistral Large 4 measured |
| Design Arena: 3D | 1253 | Not measured | Only Mistral Large 4 measured |
| Design Arena: all code categories | 1259 | Not measured | Only Mistral Large 4 measured |
| Design Arena: SVG | 1232 | Not measured | Only Mistral Large 4 measured |
| Design Arena: ASCII art | 1203 | Not measured | Only Mistral Large 4 measured |
| LiveBench design | 65.6% | Not measured | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index140
| Benchmark | Mistral Large 4 | Qwen3 32B | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.5% | Not measured | Only Mistral Large 4 measured |
| MedScribe (Vals AI) | 80.4% | Not measured | Only Mistral Large 4 measured |
| IFBench | Not measured | 36.3% | Only Qwen3 32B measured |
| Long context reasoning (AA-LCR) | 81.3% | 0.0% | Mistral Large 4 |
| DTBench | 88.2% | 67.5% | Mistral Large 4 |
| LMCA | 35.8% | 17.3% | Mistral Large 4 |
| Fiction.LiveBench | Not measured | 74.2% | Only Qwen3 32B measured |
| 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 | 1340 | Mistral Large 4 |
| LMArena Text: instruction following | 1422 | 1305 | Mistral Large 4 |
| LMArena Text: creative writing | 1363 | 1297 | Mistral Large 4 |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | 1359 | Mistral Large 4 |
| LMArena Text: non-English | 1422 | 1317 | Mistral Large 4 |
| LMArena Text: Chinese | 1492 | 1357 | Mistral Large 4 |
| LMArena Text: German | Not measured | 1341 | Only Qwen3 32B 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 | 1311 | Mistral Large 4 |
| LMArena Text: multi-turn | 1435 | 1331 | Mistral Large 4 |
| LMArena Text: longer queries | 1428 | 1327 | Mistral Large 4 |
| LMArena Text: writing and language | 1386 | 1298 | Mistral Large 4 |
| LMArena Text: entertainment and media | 1378 | 1279 | Mistral Large 4 |
| 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 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3 32B | 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$0.0034Fits in one request
Qwen3 32B$0.0002Fits in one request
Qwen3 32B costs less
Repository review
50K input + 3K output tokens
Mistral Large 4$0.081Fits in one request
Qwen3 32B$0.0048Fits in one request
Qwen3 32B costs less
Agent loop
200K input + 10K output tokens
Mistral Large 4$0.314Fits in one request
Qwen3 32B$0.019Exceeds the context window
Qwen3 32B 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 32B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | April 28, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $1.36 | $0.08 |
| Output $/Mtok | $4.18 | $0.28 |
| Coding index | 55.3 | 40.0 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Qwen3 32B for coding?
Pick Mistral Large 4 for coding: it scores 55.3 on the Vibe Coding Index against 40.0 for Qwen3 32B. Pick Qwen3 32B when output tokens cost 14.9x less.
Which is cheaper, Mistral Large 4 or Qwen3 32B?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3 32B costs $0.08 and $0.28. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 4 or Qwen3 32B?
Mistral Large 4, with 1.05M tokens against 131K.
How many benchmarks is the Mistral Large 4 vs Qwen3 32B comparison based on?
31 benchmarks have a result for both models as of October 21, 2026. Mistral Large 4's coding index rests on 2 independent benchmarks and Qwen3 32B's on 1. Where only one model has a result, the page says so instead of naming a winner.