Mistral Large 3 2512 vs Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 45.4 to 9.3, and Mistral Large 3 2512 costs 4.0x less per output token ($1.50 vs $6.00 per million). Updated October 22, 2026; 22 benchmarks have a result for both.
Mistral Large 3 2512 or Qwen3.8 Max (0902): which to pick
Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for output tokens 4.0x cheaper ($1.50 vs $6.00 per million) and a lower cost per solved task ($0.77 against $1.32).
- Shared results
- 22
- Mistral Large 3 2512 only
- 6
- Qwen3.8 Max (0902) only
- 91
- 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 Qwen3.8 Max (0902) has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 56.0 against 1.0.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 93.7% against 68.4%.
Same board, both measured
Math
AIME
No call
Only Mistral Large 3 2512 has a AIME result, 42.9%.
Directional only
Knowledge
MMLU Pro
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 88.6% against 79.8%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 1275 against 1162.
Same board, both measured
Long documents
Listed context window
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large 3 2512
Mistral Large 3 2512 $0.0013, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Mistral Large 3 2512
Mistral Large 3 2512 $0.77, Qwen3.8 Max (0902) $1.32.
Published attempt cost and pass rate
At a glance
- Coding index
- Mistral Large 3 2512 not benchmarked, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
- Widest category
- Agentic work, 55.0 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: Mistral Large 3 2512 20.1 against Qwen3.8 Max (0902) 76.2, 56.1 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Qwen3.8 Max (0902) $6.00 per million output tokens, 4.0x apart.
- Context window
- Mistral Large 3 2512 takes 262K tokens, Qwen3.8 Max (0902) 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 3 2512 | Bars | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Knowledge | 0 | 5 | ||
| Web design | 0 | 7 | ||
| General | 0 | 3 | ||
| All shared boards | 0 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | Not measured | 1674 | Only Qwen3.8 Max (0902) measured |
| AA Coding Index | 20.1 | 76.2 | Qwen3.8 Max (0902) |
| LiveCodeBench (Vals AI) | 55.3% | 87.8% | Qwen3.8 Max (0902) |
| SWE-bench Verified (Vals AI) | 41.4% | 85.6% | Qwen3.8 Max (0902) |
| Terminal-Bench 4 (Vals AI) | Not measured | 34.3% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench (Vals AI) | Not measured | 64.7% | Only Qwen3.8 Max (0902) measured |
| Code migration (Vals AI) | Not measured | 24.0% | Only Qwen3.8 Max (0902) measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 Max (0902) measured |
| IOI (Vals AI) | Not measured | 68.9% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.4% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.5% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 12.8% | Only Qwen3.8 Max (0902) measured |
| SkillsBench (Vals AI) | Not measured | 42.0% | Only Qwen3.8 Max (0902) measured |
| CyberBench (Vals AI) | Not measured | 28.6% | Only Qwen3.8 Max (0902) measured |
| SciCode | Not measured | 53.2% | Only Qwen3.8 Max (0902) measured |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| ALE-Bench | 264.7 | Not measured | Only Mistral Large 3 2512 measured |
| LMArena Text: coding | Not measured | 1502 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: software and IT | Not measured | 1498 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: React | Not measured | 1692 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: HTML | Not measured | 1649 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: from an image | Not measured | 1637 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | Not measured | 157.4 | Only Qwen3.8 Max (0902) measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 56.0 | Qwen3.8 Max (0902) |
| Design Arena: agents building web apps | Not measured | 1300 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building full-stack apps | Not measured | 1305 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building mobile apps | Not measured | 1224 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Android apps | Not measured | 1196 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Godot games | Not measured | 1234 | Only Qwen3.8 Max (0902) measured |
| Design Arena: PowerPoint slides | Not measured | 1233 | Only Qwen3.8 Max (0902) measured |
| Design Arena: spreadsheets | Not measured | 967 | Only Qwen3.8 Max (0902) measured |
| LiveBench research | Not measured | 69.9% | Only Qwen3.8 Max (0902) measured |
| LiveBench browser | Not measured | 32.0% | Only Qwen3.8 Max (0902) measured |
| LiveBench long agentic | Not measured | 42.3% | Only Qwen3.8 Max (0902) measured |
| Finance Agent (Vals AI) | Not measured | 50.6% | Only Qwen3.8 Max (0902) measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.1% | Only Qwen3.8 Max (0902) measured |
| Legal Research Bench (Vals AI) | Not measured | 47.6% | Only Qwen3.8 Max (0902) measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 60.1% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 12.9% | Only Qwen3.8 Max (0902) measured |
| APEX-Agents | Not measured | 63.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | 68.4% | 93.7% | Qwen3.8 Max (0902) |
| LiveBench reasoning | Not measured | 88.2% | Only Qwen3.8 Max (0902) measured |
| MysteryMechanism (Vals AI) | Not measured | 23.9% | Only Qwen3.8 Max (0902) measured |
| MMMU Pro (Vals AI) | 66.2% | 88.0% | Qwen3.8 Max (0902) |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.8% | Only Qwen3.8 Max (0902) measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 43.1% | Only Qwen3.8 Max (0902) measured |
| GPQA Diamond (Epoch AI run) | Not measured | 92.7% | Only Qwen3.8 Max (0902) measured |
| Chess puzzles | Not measured | 46.0% | Only Qwen3.8 Max (0902) measured |
| Mystery game puzzles | Not measured | 38.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts | Not measured | 1496 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: expert | Not measured | 1507 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts in English | Not measured | 1503 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: diagrams | Not measured | 1323 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: homework | Not measured | 1336 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AIME | 42.9% | Not measured | Only Mistral Large 3 2512 measured |
| MGSM (Vals AI) | 85.4% | Not measured | Only Mistral Large 3 2512 measured |
| OTIS Mock AIME | Not measured | 100.0% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tiers 1 to 3 | Not measured | 74.7% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only Qwen3.8 Max (0902) measured |
| ProofBench | Not measured | 58.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: math | Not measured | 1501 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: mathematical work | Not measured | 1491 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | 79.8% | 88.6% | Qwen3.8 Max (0902) |
| LegalBench (Vals AI) | 79.1% | 83.6% | Qwen3.8 Max (0902) |
| CaseLaw (Vals AI) | 61.4% | Not measured | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | 61.0% | 65.8% | Qwen3.8 Max (0902) |
| TaxEval (Vals AI) | 73.1% | 75.5% | Qwen3.8 Max (0902) |
| MortgageTax (Vals AI) | 52.1% | 64.0% | Qwen3.8 Max (0902) |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| MedCode (Vals AI) | Not measured | 40.7% | Only Qwen3.8 Max (0902) measured |
| SimpleQA Verified | Not measured | 47.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: science | Not measured | 1512 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: medicine and healthcare | Not measured | 1503 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: legal and government | Not measured | 1492 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: business and finance | Not measured | 1480 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1275 | Qwen3.8 Max (0902) |
| Design Arena: UI components | 1099 | 1338 | Qwen3.8 Max (0902) |
| Design Arena: game dev | 1080 | 1312 | Qwen3.8 Max (0902) |
| Design Arena: data viz | 1136 | 1281 | Qwen3.8 Max (0902) |
| Design Arena: 3D | 1099 | 1336 | Qwen3.8 Max (0902) |
| Design Arena: all code categories | 1141 | 1293 | Qwen3.8 Max (0902) |
| Design Arena: SVG | 992 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: ASCII art | 1069 | 1200 | Qwen3.8 Max (0902) |
| LiveBench design | Not measured | 78.6% | Only Qwen3.8 Max (0902) measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 78.4% | Only Qwen3.8 Max (0902) measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.1% | Only Qwen3.8 Max (0902) measured |
| SAGE (Vals AI) | 24.6% | 51.2% | Qwen3.8 Max (0902) |
| MedScribe (Vals AI) | Not measured | 85.0% | Only Qwen3.8 Max (0902) measured |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| Long context reasoning (AA-LCR) | Not measured | 80.3% | Only Qwen3.8 Max (0902) measured |
| DTBench | 65.1% | 92.0% | Qwen3.8 Max (0902) |
| LMCA | 16.7% | 46.2% | Qwen3.8 Max (0902) |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | Not measured | 1483 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: instruction following | Not measured | 1481 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: creative writing | Not measured | 1477 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: English | Not measured | 1491 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: non-English | Not measured | 1473 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Chinese | Not measured | 1539 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: German | Not measured | 1478 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Japanese | Not measured | 1473 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Korean | Not measured | 1460 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: French | Not measured | 1498 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Spanish | Not measured | 1489 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Russian | Not measured | 1482 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Polish | Not measured | 1471 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: multi-turn | Not measured | 1489 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: longer queries | Not measured | 1488 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: writing and language | Not measured | 1477 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: entertainment and media | Not measured | 1464 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: English | Not measured | 1311 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: Chinese | Not measured | 1358 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: humor | Not measured | 1304 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen3.8 Max (0902) | 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 3 2512 costs less
Repository review
50K input + 3K output tokens
Mistral Large 3 2512 costs less
Agent loop
200K input + 10K output tokens
Mistral Large 3 2512 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 3 2512 | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | December 1, 2025 | September 3, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.50 | $2.00 |
| Output $/Mtok | $1.50 | $6.00 |
| Coding index | Not benchmarked | 62.4 |
| Independent measurements behind it | 1 | 5 |
| Cost per solved task | $0.77 | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Qwen3.8 Max (0902) for coding?
Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for output tokens 4.0x cheaper ($1.50 vs $6.00 per million) and a lower cost per solved task ($0.77 against $1.32).
Which is cheaper, Mistral Large 3 2512 or Qwen3.8 Max (0902)?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, Mistral Large 3 2512 costs $0.77 and Qwen3.8 Max (0902) $1.32.
Which has the bigger context window, Mistral Large 3 2512 or Qwen3.8 Max (0902)?
Qwen3.8 Max (0902), with 1M tokens against 262K.
How many benchmarks is the Mistral Large 3 2512 vs Qwen3.8 Max (0902) comparison based on?
22 benchmarks have a result for both models as of October 22, 2026. Mistral Large 3 2512's coding index rests on 1 independent benchmark and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.