Mistral Large 4 vs Qwen3 235B A22B Thinking 2507
Mistral Large 4 leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 38.4 to 12.7, at about the same output price ($4.18 vs $3.50 per million). Updated October 22, 2026; 37 benchmarks have a result for both.
Mistral Large 4 or Qwen3 235B A22B Thinking 2507: which to pick
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding.
Pick Qwen3 235B A22B Thinking 2507 for output tokens 1.2x cheaper ($3.50 vs $4.18 per million) and work measured by LMArena Text: expert or SimpleQA Verified, where it leads.
- Shared results
- 37
- Mistral Large 4 only
- 45
- Qwen3 235B A22B Thinking 2507 only
- 9
- 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 Mistral Large 4 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 12.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3 235B A22B Thinking 2507 has a AA Agentic Index result, 1.3.
Directional only
Web design
Design Arena: websites
Mistral Large 4
Mistral Large 4 leads, 1258 against 1052.
Same board, both measured
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 235B A22B Thinking 2507
Mistral Large 4 $0.0034, Qwen3 235B A22B Thinking 2507 $0.0022 per turn.
List prices
At a glance
- Coding index
- Mistral Large 4 56.4 from 5 benchmarks, Qwen3 235B A22B Thinking 2507 not benchmarked.
- Widest category
- Web design, 33.6 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: UI components: Mistral Large 4 1273 against Qwen3 235B A22B Thinking 2507 942, 41.4 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 1.2x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Qwen3 235B A22B Thinking 2507 128K.
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 235B A22B Thinking 2507 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 1 | ||
| Math | 3 | 0 | ||
| Knowledge | 3 | 2 | ||
| Web design | 6 | 0 | ||
| General | 13 | 2 | ||
| All shared boards | 32 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| LiveBench coding | 60.0% | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev | 1543 | Not measured | Only Mistral Large 4 measured |
| AA Coding Index | Not measured | 22.1 | Only Qwen3 235B A22B Thinking 2507 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 |
| SciCode | 54.2% | Not measured | Only Mistral Large 4 measured |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| WeirdML | Not measured | 41.0% | Only Qwen3 235B A22B Thinking 2507 measured |
| ALE-Bench | 1213.2 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: coding | 1478 | 1424 | Mistral Large 4 |
| LMArena Text: software and IT | 1467 | 1431 | 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 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 12.7 | Mistral Large 4 |
| Epoch Capabilities Index | 150.0 | Not measured | Only Mistral Large 4 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.3 | Only Qwen3 235B A22B Thinking 2507 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% | 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 |
| Vending-Bench 2 | Not measured | -$11 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| LiveBench reasoning | 83.9% | Not measured | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | 12.2% | Not measured | Only Mistral Large 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | Not measured | Only Mistral Large 4 measured |
| GPQA Diamond (Epoch AI run) | 88.1% | 80.1% | Mistral Large 4 |
| Chess puzzles | 33.0% | Not measured | Only Mistral Large 4 measured |
| Mystery game puzzles | 17.0% | 9.0% | Mistral Large 4 |
| LMArena Text: hard prompts | 1444 | 1416 | Mistral Large 4 |
| LMArena Text: expert | 1444 | 1463 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: hard prompts in English | 1442 | 1432 | Mistral Large 4 |
| LMArena Vision: diagrams | 1288 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 86.7% | 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 | 1412 | Mistral Large 4 |
| LMArena Text: mathematical work | 1462 | 1435 | Mistral Large 4 |
| MathArena | 26.7% | 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 index32
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.7% | Not measured | Only Mistral Large 4 measured |
| SimpleQA Verified | 20.0% | 40.4% | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: science | 1448 | 1433 | Mistral Large 4 |
| LMArena Text: medicine and healthcare | 1433 | 1456 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: legal and government | 1425 | 1415 | Mistral Large 4 |
| LMArena Text: business and finance | 1439 | 1413 | Mistral Large 4 |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | 1258 | 1052 | Mistral Large 4 |
| Design Arena: UI components | 1273 | 942 | Mistral Large 4 |
| Design Arena: game dev | 1225 | 956 | Mistral Large 4 |
| Design Arena: data viz | 1275 | 950 | Mistral Large 4 |
| Design Arena: 3D | 1252 | 997 | Mistral Large 4 |
| Design Arena: all code categories | 1259 | 1032 | Mistral Large 4 |
| Design Arena: SVG | 1232 | Not measured | Only Mistral Large 4 measured |
| Design Arena: ASCII art | 1202 | 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 index132
| Benchmark | Mistral Large 4 | Qwen3 235B A22B Thinking 2507 | 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 |
| Long context reasoning (AA-LCR) | 81.3% | Not measured | Only Mistral Large 4 measured |
| DTBench | 88.2% | 80.3% | Mistral Large 4 |
| LMCA | 35.8% | 29.3% | Mistral Large 4 |
| Fiction.LiveBench | Not measured | 75.0% | Only Qwen3 235B A22B Thinking 2507 measured |
| Creative writing (Lech Mazur) | Not measured | 82.4% | Only Qwen3 235B A22B Thinking 2507 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 | 1415 | Mistral Large 4 |
| LMArena Text: instruction following | 1422 | 1386 | Mistral Large 4 |
| LMArena Text: creative writing | 1363 | 1384 | Qwen3 235B A22B Thinking 2507 |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | 1429 | Mistral Large 4 |
| LMArena Text: non-English | 1422 | 1397 | Mistral Large 4 |
| LMArena Text: Chinese | 1492 | 1481 | Mistral Large 4 |
| LMArena Text: German | Not measured | 1408 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: Japanese | 1415 | 1386 | Mistral Large 4 |
| LMArena Text: Korean | Not measured | 1375 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: French | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Spanish | 1455 | 1389 | Mistral Large 4 |
| LMArena Text: Russian | 1417 | 1401 | Mistral Large 4 |
| LMArena Text: Polish | Not measured | 1390 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: multi-turn | 1435 | 1406 | Mistral Large 4 |
| LMArena Text: longer queries | 1428 | 1400 | Mistral Large 4 |
| LMArena Text: writing and language | 1386 | 1388 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: entertainment and media | 1378 | 1370 | 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 235B A22B Thinking 2507 | 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 235B A22B Thinking 2507 costs less
Repository review
50K input + 3K output tokens
Qwen3 235B A22B Thinking 2507 costs less
Agent loop
200K input + 10K output tokens
Qwen3 235B A22B Thinking 2507 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 235B A22B Thinking 2507 |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | July 25, 2025 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $1.36 | $0.45 |
| Output $/Mtok | $4.18 | $3.50 |
| Coding index | 56.4 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Qwen3 235B A22B Thinking 2507 for coding?
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Thinking 2507 for output tokens 1.2x cheaper ($3.50 vs $4.18 per million) and work measured by LMArena Text: expert or SimpleQA Verified, where it leads.
Which is cheaper, Mistral Large 4 or Qwen3 235B A22B Thinking 2507?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 4 or Qwen3 235B A22B Thinking 2507?
Mistral Large 4, with 1.05M tokens against 128K.
How many benchmarks is the Mistral Large 4 vs Qwen3 235B A22B Thinking 2507 comparison based on?
37 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 235B A22B Thinking 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.