Mistral Large 4 vs Qwen3.6 27B
Mistral Large 4 leads Qwen3.6 27B on coding, 56.4 to 36.8 on the Vibe Coding Index, and Qwen3.6 27B costs 1.5x less per output token ($2.70 vs $4.18 per million). Updated October 23, 2026; 12 benchmarks have a result for both.
Mistral Large 4 or Qwen3.6 27B: which to pick
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 36.8 for Qwen3.6 27B.
Pick Qwen3.6 27B for output tokens 1.5x cheaper ($2.70 vs $4.18 per million).
- Shared results
- 12
- Mistral Large 4 only
- 71
- Qwen3.6 27B only
- 13
- Like-for-like categories
- 5 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 36.8.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 21.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.6 27B has a AA Agentic Index result, 18.5.
Directional only
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 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 27B
Mistral Large 4 $0.0034, Qwen3.6 27B $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.6 27B has the number, $1.30.
Directional only
At a glance
- Coding index
- Mistral Large 4 56.4 from 5 benchmarks, Qwen3.6 27B 36.8 from 2 benchmarks.
- Widest category
- Coding, 38.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Mistral Large 4 78.4% against Qwen3.6 27B 11.9%, 66.5 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3.6 27B $2.70 per million output tokens, 1.5x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Qwen3.6 27B 262K.
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 | Qwen3.6 27B | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 12 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Mistral Large 4 | Qwen3.6 27B | 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 | 53.7 | Only Qwen3.6 27B measured |
| SWE-bench Verified (Vals AI) | Not measured | 70.0% | Only Qwen3.6 27B measured |
| Terminal-Bench 4 (Vals AI) | 27.8% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 78.4% | 11.9% | Mistral Large 4 |
| 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% | 42.8% | Mistral Large 4 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.8% | Only Qwen3.6 27B 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 | 1480 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: software and IT | 1468 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: React | 1558 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | 1495 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Large 4 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 21.4 | Mistral Large 4 |
| Epoch Capabilities Index | 150.0 | 146.2 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 18.5 | Only Qwen3.6 27B 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 |
| τ²-Bench Telecom | Not measured | 94.2% | Only Qwen3.6 27B measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Mistral Large 4 | Qwen3.6 27B | 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 | 84.2% | Only Qwen3.6 27B measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 23.1% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | 88.1% | 85.9% | Mistral Large 4 |
| Chess puzzles | 33.0% | Not measured | Only Mistral Large 4 measured |
| Mystery game puzzles | 17.0% | 7.0% | Mistral Large 4 |
| LMArena Text: hard prompts | 1446 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: expert | 1449 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | 1443 | 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 | Qwen3.6 27B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 91.1% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 58.6% | 35.1% | 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 | 1467 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | 1467 | Not measured | Only Mistral Large 4 measured |
| MathArena | 26.7% | 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 index10 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.6 27B | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | Not measured | 53.2% | Only Qwen3.6 27B measured |
| CorpFin (Vals AI) | Not measured | 62.3% | Only Qwen3.6 27B measured |
| TaxEval (Vals AI) | Not measured | 71.3% | Only Qwen3.6 27B measured |
| MortgageTax (Vals AI) | Not measured | 68.3% | Only Qwen3.6 27B measured |
| 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 | 1445 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | 1432 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: legal and government | 1427 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: business and finance | 1441 | Not measured | Only Mistral Large 4 measured |
| 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 | Qwen3.6 27B | Leader |
|---|---|---|---|
| Design Arena: websites | 1258 | Not measured | Only Mistral Large 4 measured |
| Design Arena: UI components | 1273 | Not measured | Only Mistral Large 4 measured |
| Design Arena: game dev | 1226 | 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 index30
| Benchmark | Mistral Large 4 | Qwen3.6 27B | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.5% | Not measured | Only Mistral Large 4 measured |
| SAGE (Vals AI) | Not measured | 45.6% | Only Qwen3.6 27B measured |
| MedScribe (Vals AI) | 80.4% | Not measured | Only Mistral Large 4 measured |
| IFBench | Not measured | 67.6% | Only Qwen3.6 27B measured |
| Long context reasoning (AA-LCR) | 81.3% | 77.3% | Mistral Large 4 |
| DTBench | 88.2% | 78.1% | Mistral Large 4 |
| LMCA | 35.8% | 34.5% | 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 | 1432 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: instruction following | 1424 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: creative writing | 1364 | 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 | 1423 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Chinese | 1494 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Japanese | 1411 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Korean | 1366 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: French | 1489 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Spanish | 1469 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Russian | 1418 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | 1441 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: longer queries | 1429 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: writing and language | 1387 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | 1377 | 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 |
| EQ-Bench 4 | Not measured | 1026 | Only Qwen3.6 27B measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.6 27B | 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
Qwen3.6 27B costs less
Repository review
50K input + 3K output tokens
Qwen3.6 27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 27B 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 | Qwen3.6 27B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | April 27, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.36 | $0.45 |
| Output $/Mtok | $4.18 | $2.70 |
| Coding index | 56.4 | 36.8 |
| Independent measurements behind it | 5 | 2 |
| Cost per solved task | Not computable | $1.30 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Qwen3.6 27B for coding?
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 36.8 for Qwen3.6 27B. Pick Qwen3.6 27B for output tokens 1.5x cheaper ($2.70 vs $4.18 per million).
Which is cheaper, Mistral Large 4 or Qwen3.6 27B?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.
Which has the bigger context window, Mistral Large 4 or Qwen3.6 27B?
Mistral Large 4, with 1.05M tokens against 262K.
How many benchmarks is the Mistral Large 4 vs Qwen3.6 27B comparison based on?
12 benchmarks have a result for both models as of October 23, 2026. Mistral Large 4's coding index rests on 5 independent benchmarks and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.