MiniMax M2.1 vs Mistral Large 3 2512
MiniMax M2.1 leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 20.9 to 9.3, and MiniMax M2.1 costs 1.3x less per output token ($1.20 vs $1.50 per million). Updated October 22, 2026; 20 benchmarks have a result for both.
MiniMax M2.1 or Mistral Large 3 2512: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick MiniMax M2.1 for output tokens 1.3x cheaper ($1.20 vs $1.50 per million) and a lower cost per solved task ($0.59 against $0.77).
- Shared results
- 20
- MiniMax M2.1 only
- 14
- Mistral Large 3 2512 only
- 8
- 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M2.1
MiniMax M2.1 leads, 20.9 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Large 3 2512 has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
MiniMax M2.1
MiniMax M2.1 leads, 78.5% against 68.4%.
Same board, both measured
Math
AIME
MiniMax M2.1
MiniMax M2.1 leads, 77.9% against 42.9%.
Same board, both measured
Knowledge
MMLU Pro
MiniMax M2.1
MiniMax M2.1 leads, 87.0% against 79.8%.
Same board, both measured
Web design
Design Arena: websites
MiniMax M2.1
MiniMax M2.1 leads, 1201 against 1162.
Same board, both measured
Long documents
Listed context window
Mistral Large 3 2512
Mistral Large 3 2512 takes 262K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.1
MiniMax M2.1 $0.0009, Mistral Large 3 2512 $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M2.1
MiniMax M2.1 $0.59, Mistral Large 3 2512 $0.77.
Published attempt cost and pass rate
At a glance
- Coding index
- MiniMax M2.1 not benchmarked, Mistral Large 3 2512 not benchmarked.
- Widest category
- Coding, 23.9 points apart on average over 3 shared benchmarks.
- Widest single gap
- AIME: MiniMax M2.1 77.9% against Mistral Large 3 2512 42.9%, 35.0 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2.1 $1.20 against Mistral Large 3 2512 $1.50 per million output tokens, 1.3x apart.
- Context window
- MiniMax M2.1 takes 205K 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 M2.1 | Bars | Mistral Large 3 2512 | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 2 | 4 | ||
| Web design | 7 | 0 | ||
| All shared boards | 16 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 20.1 | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Vals AI) | 81.8% | 55.3% | MiniMax M2.1 |
| SWE-bench Verified (Vals AI) | 74.8% | 41.4% | MiniMax M2.1 |
| LiveCodeBench (Artificial Analysis run) | 81.0% | Not measured | Only MiniMax M2.1 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 28.8% | Not measured | Only MiniMax M2.1 measured |
| Terminal-Bench | 36.6% | Not measured | Only MiniMax M2.1 measured |
| ALE-Bench | 623.8 | 264.7 | MiniMax M2.1 |
| Neither model has a result on the other 36 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.9 | 9.3 | MiniMax M2.1 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.0 | Only Mistral Large 3 2512 measured |
| τ²-Bench Telecom | 85.4% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | 68.4% | MiniMax M2.1 |
| MMMU Pro (Vals AI) | Not measured | 66.2% | Only Mistral Large 3 2512 measured |
| GPQA Diamond (Artificial Analysis run) | 83.0% | Not measured | Only MiniMax M2.1 measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.2% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 19 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AIME | 77.9% | 42.9% | MiniMax M2.1 |
| MATH 500 (Vals AI) | 89.0% | Not measured | Only MiniMax M2.1 measured |
| MGSM (Vals AI) | 87.8% | 85.4% | MiniMax M2.1 |
| AA Math Index | 82.7 | Not measured | Only MiniMax M2.1 measured |
| AIME 2025 (Artificial Analysis run) | 82.7% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | 79.8% | MiniMax M2.1 |
| LegalBench (Vals AI) | 75.5% | 79.1% | Mistral Large 3 2512 |
| CaseLaw (Vals AI) | 55.8% | 61.4% | Mistral Large 3 2512 |
| CorpFin (Vals AI) | 58.9% | 61.0% | Mistral Large 3 2512 |
| TaxEval (Vals AI) | 66.3% | 73.1% | Mistral Large 3 2512 |
| MortgageTax (Vals AI) | Not measured | 52.1% | Only Mistral Large 3 2512 measured |
| MedQA (Vals AI) | 91.2% | 82.2% | MiniMax M2.1 |
| MedCode (Vals AI) | 34.1% | Not measured | Only MiniMax M2.1 measured |
| MMLU Pro (Artificial Analysis run) | 87.5% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1201 | 1162 | MiniMax M2.1 |
| Design Arena: UI components | 1220 | 1099 | MiniMax M2.1 |
| Design Arena: game dev | 1134 | 1079 | MiniMax M2.1 |
| Design Arena: data viz | 1206 | 1137 | MiniMax M2.1 |
| Design Arena: 3D | 1164 | 1099 | MiniMax M2.1 |
| Design Arena: all code categories | 1190 | 1141 | MiniMax M2.1 |
| Design Arena: SVG | 1131 | 992 | MiniMax M2.1 |
| Design Arena: ASCII art | Not measured | 1069 | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | MiniMax M2.1 | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 24.6% | Only Mistral Large 3 2512 measured |
| MedScribe (Vals AI) | 80.8% | Not measured | Only MiniMax M2.1 measured |
| IFBench | 69.9% | Not measured | Only MiniMax M2.1 measured |
| Long context reasoning (AA-LCR) | 67.7% | Not measured | Only MiniMax M2.1 measured |
| DTBench | Not measured | 65.1% | Only Mistral Large 3 2512 measured |
| LMCA | Not measured | 16.7% | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M2.1 | 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 M2.1 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.1 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.1 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 M2.1 | Mistral Large 3 2512 |
|---|---|---|
| Maker | MiniMax | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | December 23, 2025 | December 1, 2025 |
| Context window | 205K | 262K |
| Input $/Mtok | $0.30 | $0.50 |
| Output $/Mtok | $1.20 | $1.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.59 | $0.77 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.1 better than Mistral Large 3 2512 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M2.1 for output tokens 1.3x cheaper ($1.20 vs $1.50 per million) and a lower cost per solved task ($0.59 against $0.77).
Which is cheaper, MiniMax M2.1 or Mistral Large 3 2512?
MiniMax M2.1 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 M2.1 costs $0.59 and Mistral Large 3 2512 $0.77.
Which has the bigger context window, MiniMax M2.1 or Mistral Large 3 2512?
Mistral Large 3 2512, with 262K tokens against 205K.
How many benchmarks is the MiniMax M2.1 vs Mistral Large 3 2512 comparison based on?
20 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.1's coding index rests on 1 independent benchmark and Mistral Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.