Mistral Large 4 vs Qwen3.5-Flash
Mistral Large 4 leads Qwen3.5-Flash on coding, 56.4 to 41.1 on the Vibe Coding Index, and Qwen3.5-Flash costs 16.1x less per output token ($0.26 vs $4.18 per million). Updated October 22, 2026; 40 benchmarks have a result for both.
Mistral Large 4 or Qwen3.5-Flash: which to pick
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 41.1 for Qwen3.5-Flash.
Pick Qwen3.5-Flash for output tokens 16.1x cheaper ($0.26 vs $4.18 per million) and work measured by Mystery game puzzles or SimpleQA Verified, where it leads.
- Shared results
- 40
- Mistral Large 4 only
- 41
- Qwen3.5-Flash only
- 15
- 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
Mistral Large 4
Mistral Large 4 scores 56.4 against 41.1.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Mistral Large 4 has a AA Intelligence Index result, 38.4.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5-Flash has a GPQA Diamond result, 82.8%.
Directional only
Math
AIME
No call
Only Qwen3.5-Flash has a AIME result, 92.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5-Flash has a MMLU Pro result, 84.1%.
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
Qwen3.5-Flash
Mistral Large 4 $0.0034, Qwen3.5-Flash $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5-Flash has the number, $0.40.
Directional only
At a glance
- Coding index
- Mistral Large 4 56.4 from 5 benchmarks, Qwen3.5-Flash 41.1 from 2 benchmarks.
- Widest category
- Coding, 30.2 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Mistral Large 4 1559 against Qwen3.5-Flash 1229, 54.9 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3.5-Flash $0.26 per million output tokens, 16.1x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Qwen3.5-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 | Qwen3.5-Flash | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 5 | 1 | ||
| Math | 4 | 0 | ||
| Knowledge | 5 | 1 | ||
| General | 17 | 0 | ||
| All shared boards | 38 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | Mistral Large 4 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| LiveBench coding | 60.0% | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev | 1543 | 1244 | Mistral Large 4 |
| LiveCodeBench (Vals AI) | Not measured | 83.3% | Only Qwen3.5-Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 64.4% | Only Qwen3.5-Flash 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 | 265.9 | Mistral Large 4 |
| LMArena Text: coding | 1478 | 1412 | Mistral Large 4 |
| LMArena Text: software and IT | 1467 | 1416 | Mistral Large 4 |
| LMArena WebDev: React | 1559 | 1229 | Mistral Large 4 |
| LMArena WebDev: HTML | 1487 | 1291 | Mistral Large 4 |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 4 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | Not measured | Only Mistral Large 4 measured |
| Epoch Capabilities Index | 150.0 | 143.5 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.5-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 index51
| Benchmark | Mistral Large 4 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.8% | Only Qwen3.5-Flash measured |
| LiveBench reasoning | 83.9% | Not measured | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | 12.2% | Not measured | Only Mistral Large 4 measured |
| MMMU Pro (Vals AI) | Not measured | 81.9% | Only Qwen3.5-Flash 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% | 14.0% | Mistral Large 4 |
| Mystery game puzzles | 17.0% | 20.0% | Qwen3.5-Flash |
| LMArena Text: hard prompts | 1444 | 1403 | Mistral Large 4 |
| LMArena Text: expert | 1444 | 1407 | Mistral Large 4 |
| LMArena Text: hard prompts in English | 1442 | 1409 | 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 index40
| Benchmark | Mistral Large 4 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AIME | Not measured | 92.5% | Only Qwen3.5-Flash measured |
| OTIS Mock AIME | 98.3% | 84.4% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 58.6% | 18.2% | 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 | 1407 | Mistral Large 4 |
| LMArena Text: mathematical work | 1462 | 1413 | Mistral Large 4 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | Mistral Large 4 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.1% | Only Qwen3.5-Flash measured |
| LegalBench (Vals AI) | Not measured | 84.3% | Only Qwen3.5-Flash measured |
| CaseLaw (Vals AI) | Not measured | 56.0% | Only Qwen3.5-Flash measured |
| CorpFin (Vals AI) | Not measured | 63.6% | Only Qwen3.5-Flash measured |
| TaxEval (Vals AI) | Not measured | 72.2% | Only Qwen3.5-Flash measured |
| MortgageTax (Vals AI) | Not measured | 67.4% | Only Qwen3.5-Flash measured |
| MedCode (Vals AI) | 40.7% | 33.0% | Mistral Large 4 |
| SimpleQA Verified | 20.0% | 20.3% | Qwen3.5-Flash |
| LMArena Text: science | 1448 | 1415 | Mistral Large 4 |
| LMArena Text: medicine and healthcare | 1433 | 1407 | Mistral Large 4 |
| LMArena Text: legal and government | 1425 | 1398 | Mistral Large 4 |
| LMArena Text: business and finance | 1439 | 1394 | Mistral Large 4 |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.5-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 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
| Benchmark | Mistral Large 4 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.5% | Not measured | Only Mistral Large 4 measured |
| SAGE (Vals AI) | Not measured | 42.5% | Only Qwen3.5-Flash measured |
| MedScribe (Vals AI) | 80.4% | 70.6% | Mistral Large 4 |
| Long context reasoning (AA-LCR) | 81.3% | Not measured | Only Mistral Large 4 measured |
| DTBench | 88.2% | 82.9% | Mistral Large 4 |
| LMCA | 35.8% | 29.1% | Mistral Large 4 |
| 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 | 1397 | Mistral Large 4 |
| LMArena Text: instruction following | 1422 | 1374 | Mistral Large 4 |
| LMArena Text: creative writing | 1363 | 1343 | Mistral Large 4 |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | 1404 | Mistral Large 4 |
| LMArena Text: non-English | 1422 | 1385 | Mistral Large 4 |
| LMArena Text: Chinese | 1492 | 1445 | Mistral Large 4 |
| LMArena Text: German | Not measured | 1390 | Only Qwen3.5-Flash measured |
| LMArena Text: Japanese | 1415 | 1369 | Mistral Large 4 |
| LMArena Text: Korean | Not measured | 1344 | Only Qwen3.5-Flash measured |
| LMArena Text: French | 1492 | 1413 | Mistral Large 4 |
| LMArena Text: Spanish | 1455 | 1400 | Mistral Large 4 |
| LMArena Text: Russian | 1417 | 1380 | Mistral Large 4 |
| LMArena Text: Polish | Not measured | 1376 | Only Qwen3.5-Flash measured |
| LMArena Text: multi-turn | 1435 | 1393 | Mistral Large 4 |
| LMArena Text: longer queries | 1428 | 1392 | Mistral Large 4 |
| LMArena Text: writing and language | 1386 | 1369 | Mistral Large 4 |
| LMArena Text: entertainment and media | 1378 | 1347 | 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 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.5-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
Qwen3.5-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-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 | Qwen3.5-Flash |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | October 6, 2026 | February 25, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.36 | $0.065 |
| Output $/Mtok | $4.18 | $0.26 |
| Coding index | 56.4 | 41.1 |
| Independent measurements behind it | 5 | 2 |
| Cost per solved task | Not computable | $0.40 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Qwen3.5-Flash for coding?
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 41.1 for Qwen3.5-Flash. Pick Qwen3.5-Flash for output tokens 16.1x cheaper ($0.26 vs $4.18 per million) and work measured by Mystery game puzzles or SimpleQA Verified, where it leads.
Which is cheaper, Mistral Large 4 or Qwen3.5-Flash?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.
Which has the bigger context window, Mistral Large 4 or Qwen3.5-Flash?
Mistral Large 4, with 1.05M tokens against 1M.
How many benchmarks is the Mistral Large 4 vs Qwen3.5-Flash comparison based on?
40 benchmarks have a result for both models as of October 22, 2026. Mistral Large 4's coding index rests on 5 independent benchmarks and Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.