MiniMax M3 vs Mistral Large 3 2512
MiniMax M3 leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 29.2 to 9.3, and MiniMax M3 costs 1.3x less per output token ($1.20 vs $1.50 per million). Updated October 22, 2026; 24 benchmarks have a result for both.
MiniMax M3 or Mistral Large 3 2512: which to pick
Only MiniMax M3 has a coding score, 39.2 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 work measured by TaxEval (Vals AI), where it leads.
- Shared results
- 24
- MiniMax M3 only
- 92
- Mistral Large 3 2512 only
- 4
- 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 MiniMax M3 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M3
MiniMax M3 leads, 29.2 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
MiniMax M3
MiniMax M3 leads, 29.5 against 1.0.
Same board, both measured
Reasoning
GPQA Diamond
MiniMax M3
MiniMax M3 leads, 92.7% 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
MiniMax M3
MiniMax M3 leads, 84.2% against 79.8%.
Same board, both measured
Web design
Design Arena: websites
MiniMax M3
MiniMax M3 leads, 1257 against 1162.
Same board, both measured
Long documents
Listed context window
MiniMax M3
MiniMax M3 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M3
MiniMax M3 $0.0009, Mistral Large 3 2512 $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M3
MiniMax M3 $0.56, Mistral Large 3 2512 $0.77.
Published attempt cost and pass rate
At a glance
- Coding index
- MiniMax M3 39.2 from 6 benchmarks, Mistral Large 3 2512 not benchmarked.
- Widest category
- Agentic work, 28.5 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: MiniMax M3 58.6 against Mistral Large 3 2512 20.1, 38.5 points apart on a 0 to 100 scale.
- Output price
- MiniMax M3 $1.20 against Mistral Large 3 2512 $1.50 per million output tokens, 1.3x apart.
- Context window
- MiniMax M3 takes 1.05M tokens, Mistral Large 3 2512 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 | MiniMax M3 | Bars | Mistral Large 3 2512 | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Knowledge | 4 | 1 | ||
| Web design | 8 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 23 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| LiveBench coding | 70.9% | Not measured | Only MiniMax M3 measured |
| LMArena WebDev | 1482 | Not measured | Only MiniMax M3 measured |
| AA Coding Index | 58.6 | 20.1 | MiniMax M3 |
| LiveCodeBench (Vals AI) | 82.2% | 55.3% | MiniMax M3 |
| SWE-bench Verified (Vals AI) | 75.0% | 41.4% | MiniMax M3 |
| Terminal-Bench 4 (Vals AI) | 1.0% | Not measured | Only MiniMax M3 measured |
| Vibe Code Bench (Vals AI) | 47.6% | Not measured | Only MiniMax M3 measured |
| Code migration (Vals AI) | 19.9% | Not measured | Only MiniMax M3 measured |
| Terminal-Bench 2.1 (Vals AI) | 53.6% | Not measured | Only MiniMax M3 measured |
| SWE-bench Multimodal (Vals AI) | 33.3% | Not measured | Only MiniMax M3 measured |
| Vibe Code Bench 1-100 (Vals AI) | 9.2% | Not measured | Only MiniMax M3 measured |
| SkillsBench (Vals AI) | 51.5% | Not measured | Only MiniMax M3 measured |
| CyberBench (Vals AI) | 65.0% | Not measured | Only MiniMax M3 measured |
| SciCode | 47.1% | Not measured | Only MiniMax M3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | Not measured | Only MiniMax M3 measured |
| FrontierCode | 14.7% | Not measured | Only MiniMax M3 measured |
| ALE-Bench | 640.0 | 264.7 | MiniMax M3 |
| LMArena Text: coding | 1470 | Not measured | Only MiniMax M3 measured |
| LMArena Text: software and IT | 1466 | Not measured | Only MiniMax M3 measured |
| LMArena WebDev: React | 1478 | Not measured | Only MiniMax M3 measured |
| LMArena WebDev: HTML | 1455 | Not measured | Only MiniMax M3 measured |
| LMArena WebDev: from an image | 1470 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 29.2 | 9.3 | MiniMax M3 |
| Epoch Capabilities Index | 146.9 | Not measured | Only MiniMax M3 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | 29.5 | 1.0 | MiniMax M3 |
| Design Arena: agents building web apps | 1200 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building full-stack apps | 1197 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building mobile apps | 1169 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building Android apps | 1159 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building games | 1158 | Not measured | Only MiniMax M3 measured |
| Design Arena: HTML slides | 1130 | Not measured | Only MiniMax M3 measured |
| Design Arena: PowerPoint slides | 1181 | Not measured | Only MiniMax M3 measured |
| Design Arena: spreadsheets | 1028 | Not measured | Only MiniMax M3 measured |
| LiveBench research | 68.0% | Not measured | Only MiniMax M3 measured |
| LiveBench browser | 8.0% | Not measured | Only MiniMax M3 measured |
| LiveBench long agentic | 12.4% | Not measured | Only MiniMax M3 measured |
| Finance Agent (Vals AI) | 48.3% | Not measured | Only MiniMax M3 measured |
| Tax Agent Bench (Vals AI) | 20.6% | Not measured | Only MiniMax M3 measured |
| Legal Research Bench (Vals AI) | 29.8% | Not measured | Only MiniMax M3 measured |
| Excel Modeling Benchmark (Vals AI) | 47.8% | Not measured | Only MiniMax M3 measured |
| τ²-Bench Telecom | 88.9% | Not measured | Only MiniMax M3 measured |
| APEX-Agents | 37.7% | Not measured | Only MiniMax M3 measured |
| OSWorld 2.0 | 4.6% | Not measured | Only MiniMax M3 measured |
| Vending-Bench 2 | $2,158 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | 68.4% | MiniMax M3 |
| LiveBench reasoning | 74.5% | Not measured | Only MiniMax M3 measured |
| MMMU Pro (Vals AI) | 81.2% | 66.2% | MiniMax M3 |
| GPQA Diamond (Artificial Analysis run) | 92.9% | Not measured | Only MiniMax M3 measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.0% | Not measured | Only MiniMax M3 measured |
| GPQA Diamond (Epoch AI run) | 90.9% | Not measured | Only MiniMax M3 measured |
| SimpleBench | 45.8% | Not measured | Only MiniMax M3 measured |
| Chess puzzles | 13.0% | Not measured | Only MiniMax M3 measured |
| Mystery game puzzles | 8.0% | Not measured | Only MiniMax M3 measured |
| LMArena Text: hard prompts | 1447 | Not measured | Only MiniMax M3 measured |
| LMArena Text: expert | 1461 | Not measured | Only MiniMax M3 measured |
| LMArena Text: hard prompts in English | 1455 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: diagrams | 1266 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: homework | 1268 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AIME | Not measured | 42.9% | Only Mistral Large 3 2512 measured |
| MGSM (Vals AI) | Not measured | 85.4% | Only Mistral Large 3 2512 measured |
| OTIS Mock AIME | 71.1% | Not measured | Only MiniMax M3 measured |
| ProofBench | 18.0% | Not measured | Only MiniMax M3 measured |
| LMArena Text: math | 1429 | Not measured | Only MiniMax M3 measured |
| LMArena Text: mathematical work | 1448 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| MMLU Pro | 84.2% | 79.8% | MiniMax M3 |
| LegalBench (Vals AI) | 85.4% | 79.1% | MiniMax M3 |
| CaseLaw (Vals AI) | Not measured | 61.4% | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | 68.1% | 61.0% | MiniMax M3 |
| TaxEval (Vals AI) | 72.7% | 73.1% | Mistral Large 3 2512 |
| MortgageTax (Vals AI) | 68.4% | 52.1% | MiniMax M3 |
| MedQA (Vals AI) | Not measured | 82.2% | Only Mistral Large 3 2512 measured |
| MedCode (Vals AI) | 46.3% | Not measured | Only MiniMax M3 measured |
| LMArena Text: science | 1452 | Not measured | Only MiniMax M3 measured |
| LMArena Text: medicine and healthcare | 1441 | Not measured | Only MiniMax M3 measured |
| LMArena Text: legal and government | 1437 | Not measured | Only MiniMax M3 measured |
| LMArena Text: business and finance | 1434 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1257 | 1162 | MiniMax M3 |
| Design Arena: UI components | 1242 | 1099 | MiniMax M3 |
| Design Arena: game dev | 1210 | 1080 | MiniMax M3 |
| Design Arena: data viz | 1236 | 1136 | MiniMax M3 |
| Design Arena: 3D | 1208 | 1099 | MiniMax M3 |
| Design Arena: all code categories | 1247 | 1141 | MiniMax M3 |
| Design Arena: SVG | 1161 | 992 | MiniMax M3 |
| Design Arena: ASCII art | 1161 | 1069 | MiniMax M3 |
| LiveBench design | 66.2% | Not measured | Only MiniMax M3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.2% | Not measured | Only MiniMax M3 measured |
| Public Benefits Bench (Vals AI) | 64.1% | Not measured | Only MiniMax M3 measured |
| SAGE (Vals AI) | 50.6% | 24.6% | MiniMax M3 |
| MedScribe (Vals AI) | 87.3% | Not measured | Only MiniMax M3 measured |
| Vals Multimodal Index | 60.0% | Not measured | Only MiniMax M3 measured |
| IFBench | 82.9% | Not measured | Only MiniMax M3 measured |
| Long context reasoning (AA-LCR) | 83.0% | Not measured | Only MiniMax M3 measured |
| DTBench | 78.9% | 65.1% | MiniMax M3 |
| LMCA | 33.7% | 16.7% | MiniMax M3 |
| Surface Evolver Bench | 55.0% | Not measured | Only MiniMax M3 measured |
| LMArena Text | 1433 | Not measured | Only MiniMax M3 measured |
| LMArena Text: instruction following | 1433 | Not measured | Only MiniMax M3 measured |
| LMArena Text: creative writing | 1404 | Not measured | Only MiniMax M3 measured |
| LMArena Vision | 1251 | Not measured | Only MiniMax M3 measured |
| LMArena Text: English | 1443 | Not measured | Only MiniMax M3 measured |
| LMArena Text: non-English | 1420 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Chinese | 1466 | Not measured | Only MiniMax M3 measured |
| LMArena Text: German | 1428 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Japanese | 1380 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Korean | 1373 | Not measured | Only MiniMax M3 measured |
| LMArena Text: French | 1444 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Spanish | 1433 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Russian | 1426 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Polish | 1423 | Not measured | Only MiniMax M3 measured |
| LMArena Text: multi-turn | 1443 | Not measured | Only MiniMax M3 measured |
| LMArena Text: longer queries | 1446 | Not measured | Only MiniMax M3 measured |
| LMArena Text: writing and language | 1419 | Not measured | Only MiniMax M3 measured |
| LMArena Text: entertainment and media | 1403 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: English | 1263 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: Chinese | 1311 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: reading text | 1259 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: humor | 1235 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: recognizing things | 1197 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: creative writing | 1234 | Not measured | Only MiniMax M3 measured |
| LMArena Document | 1435 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M3 | Mistral Large 3 2512 | 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
MiniMax M3 costs less
Repository review
50K input + 3K output tokens
MiniMax M3 costs less
Agent loop
200K input + 10K output tokens
MiniMax M3 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 | MiniMax M3 | Mistral Large 3 2512 |
|---|---|---|
| Maker | MiniMax | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | May 31, 2026 | December 1, 2025 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.30 | $0.50 |
| Output $/Mtok | $1.20 | $1.50 |
| Coding index | 39.2 | Not benchmarked |
| Independent measurements behind it | 6 | 1 |
| Cost per solved task | $0.56 | $0.77 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M3 better than Mistral Large 3 2512 for coding?
Only MiniMax M3 has a coding score, 39.2 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 work measured by TaxEval (Vals AI), where it leads.
Which is cheaper, MiniMax M3 or Mistral Large 3 2512?
MiniMax M3 costs $0.30 per million input tokens and $1.20 per million output tokens; Mistral Large 3 2512 costs $0.50 and $1.50. Per solved SWE-bench Verified task, MiniMax M3 costs $0.56 and Mistral Large 3 2512 $0.77.
Which has the bigger context window, MiniMax M3 or Mistral Large 3 2512?
MiniMax M3, with 1.05M tokens against 262K.
How many benchmarks is the MiniMax M3 vs Mistral Large 3 2512 comparison based on?
24 benchmarks have a result for both models as of October 22, 2026. MiniMax M3's coding index rests on 6 independent benchmarks and Mistral Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.