Command A vs MiniMax M2.1
MiniMax M2.1 leads Command A on the Artificial Analysis Intelligence Index, 20.9 to 13.1, and MiniMax M2.1 costs 8.3x less per output token ($1.20 vs $10.00 per million). Updated October 21, 2026; 25 benchmarks have a result for both.
Command A or MiniMax M2.1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Command A for a larger context window (256K against 205K tokens) and work measured by LiveCodeBench (Vals AI) or SWE-bench Verified (Vals AI), where it leads.
- Shared results
- 25
- Command A only
- 37
- MiniMax M2.1 only
- 9
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M2.1
MiniMax M2.1 leads, 20.9 against 13.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Command A has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
MiniMax M2.1
MiniMax M2.1 leads, 78.5% against 48.5%.
Same board, both measured
Math
AIME
MiniMax M2.1
MiniMax M2.1 leads, 77.9% against 13.3%.
Same board, both measured
Knowledge
MMLU Pro
MiniMax M2.1
MiniMax M2.1 leads, 87.0% against 69.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiniMax M2.1 has a Design Arena: websites result, 1201.
Directional only
Long documents
Listed context window
Command A
Command A takes 256K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.1
Command A $0.0075, MiniMax M2.1 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M2.1
Command A $2.69, MiniMax M2.1 $0.59.
Published attempt cost and pass rate
At a glance
- Coding index
- Command A not benchmarked, MiniMax M2.1 not benchmarked.
- Widest category
- Math, 43.8 points apart on average over 5 shared benchmarks.
- Widest single gap
- AA Math Index: Command A 13.0 against MiniMax M2.1 82.7, 69.7 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against MiniMax M2.1 $1.20 per million output tokens, 8.3x apart.
- Context window
- Command A takes 256K tokens, MiniMax M2.1 205K.
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 | Command A | Bars | MiniMax M2.1 | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 5 | ||
| Knowledge | 2 | 6 | ||
| General | 1 | 2 | ||
| All shared boards | 3 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Coding Index | 27.8 | Not measured | Only Command A measured |
| LiveCodeBench (Vals AI) | 35.1% | 81.8% | MiniMax M2.1 |
| SWE-bench Verified (Vals AI) | 7.8% | 74.8% | MiniMax M2.1 |
| Terminal-Bench 2.1 (Vals AI) | 17.6% | Not measured | Only Command A measured |
| LiveCodeBench (Artificial Analysis run) | 28.7% | 81.0% | MiniMax M2.1 |
| SciCode | 38.5% | Not measured | Only Command A measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 28.8% | MiniMax M2.1 |
| Terminal-Bench | Not measured | 36.6% | Only MiniMax M2.1 measured |
| ALE-Bench | Not measured | 623.8 | Only MiniMax M2.1 measured |
| LMArena Text: coding | 1330 | Not measured | Only Command A measured |
| LMArena Text: software and IT | 1336 | Not measured | Only Command A measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 20.9 | MiniMax M2.1 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Command A measured |
| Finance Agent (Vals AI) | 9.0% | Not measured | Only Command A measured |
| τ²-Bench Telecom | 80.7% | 85.4% | MiniMax M2.1 |
| Berkeley Function Calling Leaderboard (BFCL) | 46.5% | Not measured | Only Command A measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | 78.5% | MiniMax M2.1 |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 83.0% | MiniMax M2.1 |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 23.2% | MiniMax M2.1 |
| LMArena Text: hard prompts | 1326 | Not measured | Only Command A measured |
| LMArena Text: expert | 1296 | Not measured | Only Command A measured |
| LMArena Text: hard prompts in English | 1335 | Not measured | Only Command A measured |
| Kagi LLM Benchmark | 28.8% | Not measured | Only Command A measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| AIME | 13.3% | 77.9% | MiniMax M2.1 |
| MATH 500 (Vals AI) | 76.2% | 89.0% | MiniMax M2.1 |
| MGSM (Vals AI) | 85.7% | 87.8% | MiniMax M2.1 |
| AA Math Index | 13.0 | 82.7 | MiniMax M2.1 |
| AIME 2025 (Artificial Analysis run) | 13.0% | 82.7% | MiniMax M2.1 |
| LMArena Text: math | 1300 | Not measured | Only Command A measured |
| LMArena Text: mathematical work | 1312 | Not measured | Only Command A measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index26
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| MMLU Pro | 69.2% | 87.0% | MiniMax M2.1 |
| LegalBench (Vals AI) | 79.7% | 75.5% | Command A |
| CaseLaw (Vals AI) | 64.5% | 55.8% | Command A |
| CorpFin (Vals AI) | 46.0% | 58.9% | MiniMax M2.1 |
| TaxEval (Vals AI) | 61.4% | 66.3% | MiniMax M2.1 |
| MedQA (Vals AI) | 80.5% | 91.2% | MiniMax M2.1 |
| MedCode (Vals AI) | 19.7% | 34.1% | MiniMax M2.1 |
| MMLU Pro (Artificial Analysis run) | 71.2% | 87.5% | MiniMax M2.1 |
| LMArena Text: science | 1339 | Not measured | Only Command A measured |
| LMArena Text: medicine and healthcare | 1334 | Not measured | Only Command A measured |
| LMArena Text: legal and government | 1348 | Not measured | Only Command A measured |
| LMArena Text: business and finance | 1315 | Not measured | Only Command A measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1201 | Only MiniMax M2.1 measured |
| Design Arena: UI components | Not measured | 1223 | Only MiniMax M2.1 measured |
| Design Arena: game dev | Not measured | 1134 | Only MiniMax M2.1 measured |
| Design Arena: data viz | Not measured | 1206 | Only MiniMax M2.1 measured |
| Design Arena: 3D | Not measured | 1165 | Only MiniMax M2.1 measured |
| Design Arena: all code categories | Not measured | 1190 | Only MiniMax M2.1 measured |
| Design Arena: SVG | Not measured | 1132 | Only MiniMax M2.1 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Command A | MiniMax M2.1 | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | 80.8% | MiniMax M2.1 |
| IFBench | 73.9% | 69.9% | Command A |
| Long context reasoning (AA-LCR) | 52.7% | 67.7% | MiniMax M2.1 |
| DTBench | 61.3% | Not measured | Only Command A measured |
| LMCA | 10.3% | Not measured | Only Command A measured |
| LMArena Text | 1331 | Not measured | Only Command A measured |
| LMArena Text: instruction following | 1309 | Not measured | Only Command A measured |
| LMArena Text: creative writing | 1319 | Not measured | Only Command A measured |
| LMArena Text: English | 1344 | Not measured | Only Command A measured |
| LMArena Text: non-English | 1313 | Not measured | Only Command A measured |
| LMArena Text: Chinese | 1327 | Not measured | Only Command A measured |
| LMArena Text: German | 1342 | Not measured | Only Command A measured |
| LMArena Text: Japanese | 1285 | Not measured | Only Command A measured |
| LMArena Text: Korean | 1285 | Not measured | Only Command A measured |
| LMArena Text: French | 1351 | Not measured | Only Command A measured |
| LMArena Text: Spanish | 1347 | Not measured | Only Command A measured |
| LMArena Text: Russian | 1314 | Not measured | Only Command A measured |
| LMArena Text: Polish | 1324 | Not measured | Only Command A measured |
| LMArena Text: multi-turn | 1338 | Not measured | Only Command A measured |
| LMArena Text: longer queries | 1334 | Not measured | Only Command A measured |
| LMArena Text: writing and language | 1328 | Not measured | Only Command A measured |
| LMArena Text: entertainment and media | 1306 | Not measured | Only Command A measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | MiniMax M2.1 | 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 | Cohere Command A | MiniMax M2.1 |
|---|---|---|
| Maker | Cohere | MiniMax |
| Weights | Open weights | Open weights |
| Released | March 13, 2025 | December 23, 2025 |
| Context window | 256K | 205K |
| Input $/Mtok | $2.50 | $0.30 |
| Output $/Mtok | $10.00 | $1.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $2.69 | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Command A better than MiniMax M2.1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command A for a larger context window (256K against 205K tokens) and work measured by LiveCodeBench (Vals AI) or SWE-bench Verified (Vals AI), where it leads.
Which is cheaper, Command A or MiniMax M2.1?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Per solved SWE-bench Verified task, Command A costs $2.69 and MiniMax M2.1 $0.59.
Which has the bigger context window, Command A or MiniMax M2.1?
Command A, with 256K tokens against 205K.
How many benchmarks is the Command A vs MiniMax M2.1 comparison based on?
25 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and MiniMax M2.1's on 1. Where only one model has a result, the page says so instead of naming a winner.