Mistral Large 4 vs Qwen3.7 Flash
Qwen3.7 Flash costs 32.2x less per output token than Mistral Large 4 ($0.13 vs $4.18 per million). Updated October 22, 2026; 6 benchmarks have a result for both.
Mistral Large 4 or Qwen3.7 Flash: which to pick
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Qwen3.7 Flash has none, so the two cannot be ranked on coding.
Pick Qwen3.7 Flash for output tokens 32.2x cheaper ($0.13 vs $4.18 per million).
- Shared results
- 6
- Mistral Large 4 only
- 75
- Qwen3.7 Flash only
- 0
- 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
Only Mistral Large 4 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Mistral Large 4 has a AA Intelligence Index result, 38.4.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Large 4 has a Design Arena: websites result, 1257.
Directional only
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Flash
Mistral Large 4 $0.0034, Qwen3.7 Flash $0.0001 per turn.
List prices
At a glance
- Coding index
- Mistral Large 4 56.4 from 5 benchmarks, Qwen3.7 Flash not benchmarked.
- Widest category
- Coding, 26.4 points apart on average over 1 shared benchmark.
- Widest single gap
- FrontierMath, tiers 1 to 3: Mistral Large 4 58.6% against Qwen3.7 Flash 19.3%, 39.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3.7 Flash $0.13 per million output tokens, 32.2x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Qwen3.7 Flash 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 4 | Bars | Qwen3.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| All shared boards | 6 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | Leader |
|---|---|---|---|
| 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 |
| SciCode | 54.2% | Not measured | Only Mistral Large 4 measured |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| ALE-Bench | 1213.2 | 420.1 | Mistral Large 4 |
| LMArena Text: coding | 1478 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: software and IT | 1467 | Not measured | Only Mistral Large 4 measured |
| 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 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | Not measured | Only Mistral Large 4 measured |
| Epoch Capabilities Index | 150.0 | 144.1 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | 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 |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | 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% | 82.3% | Mistral Large 4 |
| Chess puzzles | 33.0% | Not measured | Only Mistral Large 4 measured |
| Mystery game puzzles | 17.0% | 15.0% | Mistral Large 4 |
| LMArena Text: hard prompts | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: expert | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | 1442 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: diagrams | 1288 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 86.7% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 58.6% | 19.3% | Mistral Large 4 |
| 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 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | 1462 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.7% | Not measured | Only Mistral Large 4 measured |
| SimpleQA Verified | 20.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: science | 1448 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: legal and government | 1425 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: business and finance | 1439 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1257 | Not measured | Only Mistral Large 4 measured |
| Design Arena: UI components | 1272 | Not measured | Only Mistral Large 4 measured |
| Design Arena: game dev | 1225 | Not measured | Only Mistral Large 4 measured |
| Design Arena: data viz | 1275 | Not measured | Only Mistral Large 4 measured |
| Design Arena: 3D | 1252 | 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 | 1202 | Not measured | Only Mistral Large 4 measured |
| LiveBench design | 65.6% | Not measured | Only Mistral Large 4 measured |
GeneralDirectional onlyPublic boards, shown as published, kept out of the index24 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | 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% | Not measured | Only Mistral Large 4 measured |
| LMCA | 35.8% | Not measured | Only Mistral Large 4 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 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: instruction following | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: creative writing | 1363 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: non-English | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Chinese | 1492 | Not measured | Only Mistral Large 4 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 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | 1435 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: longer queries | 1428 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: writing and language | 1386 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | 1378 | Not measured | Only Mistral Large 4 measured |
| 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 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.7 Flash | 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 Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.7 Flash 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 | Qwen3.7 Flash |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | October 6, 2026 | July 27, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.36 | $0.03 |
| Output $/Mtok | $4.18 | $0.13 |
| 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 Qwen3.7 Flash for coding?
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Qwen3.7 Flash has none, so the two cannot be ranked on coding. Pick Qwen3.7 Flash for output tokens 32.2x cheaper ($0.13 vs $4.18 per million).
Which is cheaper, Mistral Large 4 or Qwen3.7 Flash?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3.7 Flash costs $0.03 and $0.13. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 4 or Qwen3.7 Flash?
Mistral Large 4, with 1.05M tokens against 1M.
How many benchmarks is the Mistral Large 4 vs Qwen3.7 Flash comparison based on?
6 benchmarks have a result for both models as of October 22, 2026. Mistral Large 4's coding index rests on 5 independent benchmarks and Qwen3.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.