Command A vs MiniMax M2
Updated October 21, 2026. 37 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Command A has the edge where the context window is larger, 256K against 205K tokens, and where what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 37
- Command A only
- 23
- MiniMax M2 only
- 12
- Like-for-like categories
- 7 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
MiniMax M2 leads, 18.6 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
No call
Only Command A has a GPQA Diamond result, 48.5%.
Directional only
Math
AIME
No call
Only Command A has a AIME result, 13.3%.
Directional only
Knowledge
MMLU Pro
No call
Only Command A has a MMLU Pro result, 69.2%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2 has a Design Arena: websites result, 1143.
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
Command A $0.0075, MiniMax M2 $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M2
Command A $2.69, MiniMax M2 $0.702.
Published attempt cost and pass rate
At a glance
- Coding index
- Command A not benchmarked, MiniMax M2 not benchmarked.
- Widest category
- Math, 37.1 points apart on average over 4 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): Command A 13.0% against MiniMax M2 78.3%, 65.3 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against MiniMax M2 $1.02 per million output tokens, 9.8x apart.
- Context window
- Command A takes 256K tokens, MiniMax M2 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 | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 4 | ||
| Knowledge | 0 | 5 | ||
| General | 8 | 9 | ||
| All shared boards | 8 | 29 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | Command A | MiniMax M2 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 61.0% | Only MiniMax M2 measured |
| LMArena WebDev | Not measured | 1297 | Only MiniMax M2 measured |
| AA Coding Index | 27.8 | Not measured | Only Command A measured |
| LiveCodeBench (Vals AI) | 35.1% | Not measured | Only Command A measured |
| SWE-bench Verified (Vals AI) | 7.8% | Not measured | Only Command A measured |
| Terminal-Bench 2.1 (Vals AI) | 17.6% | Not measured | Only Command A measured |
| LiveCodeBench (Artificial Analysis run) | 28.7% | 82.6% | MiniMax M2 |
| SciCode | 38.5% | Not measured | Only Command A measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 25.8% | MiniMax M2 |
| Terminal-Bench | Not measured | 30.0% | Only MiniMax M2 measured |
| LMArena Text: coding | 1330 | 1371 | MiniMax M2 |
| LMArena Text: software and IT | 1336 | 1373 | MiniMax M2 |
| LMArena WebDev: HTML | Not measured | 1306 | Only MiniMax M2 measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Command A | MiniMax M2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 18.6 | MiniMax M2 |
| 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 | 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% | 86.8% | MiniMax M2 |
| Vending-Bench 2 | Not measured | $161 | Only MiniMax M2 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Command A | MiniMax M2 | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | Not measured | Only Command A measured |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 77.7% | MiniMax M2 |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 13.7% | MiniMax M2 |
| LMArena Text: hard prompts | 1326 | 1357 | MiniMax M2 |
| LMArena Text: expert | 1296 | 1338 | MiniMax M2 |
| LMArena Text: hard prompts in English | 1335 | 1376 | MiniMax M2 |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Command A | MiniMax M2 | Leader |
|---|---|---|---|
| AIME | 13.3% | Not measured | Only Command A measured |
| MATH 500 (Vals AI) | 76.2% | Not measured | Only Command A measured |
| MGSM (Vals AI) | 85.7% | Not measured | Only Command A measured |
| AA Math Index | 13.0 | 78.3 | MiniMax M2 |
| AIME 2025 (Artificial Analysis run) | 13.0% | 78.3% | MiniMax M2 |
| LMArena Text: math | 1300 | 1351 | MiniMax M2 |
| LMArena Text: mathematical work | 1312 | 1368 | MiniMax M2 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Command A | MiniMax M2 | Leader |
|---|---|---|---|
| MMLU Pro | 69.2% | Not measured | Only Command A measured |
| LegalBench (Vals AI) | 79.7% | Not measured | Only Command A measured |
| CaseLaw (Vals AI) | 64.5% | Not measured | Only Command A measured |
| CorpFin (Vals AI) | 46.0% | Not measured | Only Command A measured |
| TaxEval (Vals AI) | 61.4% | Not measured | Only Command A measured |
| MedQA (Vals AI) | 80.5% | Not measured | Only Command A measured |
| MedCode (Vals AI) | 19.7% | Not measured | Only Command A measured |
| MMLU Pro (Artificial Analysis run) | 71.2% | 82.0% | MiniMax M2 |
| LMArena Text: science | 1339 | 1348 | MiniMax M2 |
| LMArena Text: medicine and healthcare | 1334 | 1367 | MiniMax M2 |
| LMArena Text: legal and government | 1348 | 1349 | MiniMax M2 |
| LMArena Text: business and finance | 1315 | 1336 | MiniMax M2 |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Command A | MiniMax M2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1143 | Only MiniMax M2 measured |
| Design Arena: UI components | Not measured | 1136 | Only MiniMax M2 measured |
| Design Arena: game dev | Not measured | 1118 | Only MiniMax M2 measured |
| Design Arena: data viz | Not measured | 1140 | Only MiniMax M2 measured |
| Design Arena: 3D | Not measured | 1098 | Only MiniMax M2 measured |
| Design Arena: all code categories | Not measured | 1135 | Only MiniMax M2 measured |
| Design Arena: SVG | Not measured | 1100 | Only MiniMax M2 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index89
| Benchmark | Command A | MiniMax M2 | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | Not measured | Only Command A measured |
| IFBench | 73.9% | 72.3% | Command A |
| Long context reasoning (AA-LCR) | 52.7% | 64.3% | MiniMax M2 |
| DTBench | 61.3% | Not measured | Only Command A measured |
| LMCA | 10.3% | Not measured | Only Command A measured |
| LMArena Text | 1331 | 1340 | MiniMax M2 |
| LMArena Text: instruction following | 1309 | 1329 | MiniMax M2 |
| LMArena Text: creative writing | 1319 | 1286 | Command A |
| LMArena Text: English | 1344 | 1364 | MiniMax M2 |
| LMArena Text: non-English | 1313 | 1313 | MiniMax M2 |
| LMArena Text: Chinese | 1327 | 1366 | MiniMax M2 |
| LMArena Text: German | 1342 | 1357 | MiniMax M2 |
| LMArena Text: Japanese | 1285 | Not measured | Only Command A measured |
| LMArena Text: Korean | 1285 | Not measured | Only Command A measured |
| LMArena Text: French | 1351 | 1336 | Command A |
| LMArena Text: Spanish | 1347 | 1326 | Command A |
| LMArena Text: Russian | 1314 | 1330 | MiniMax M2 |
| LMArena Text: Polish | 1324 | 1312 | Command A |
| LMArena Text: multi-turn | 1338 | 1361 | MiniMax M2 |
| LMArena Text: longer queries | 1334 | 1331 | Command A |
| LMArena Text: writing and language | 1328 | 1295 | Command A |
| LMArena Text: entertainment and media | 1306 | 1298 | Command A |
| 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 | 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 costs less
Repository review
50K input + 3K output tokens
MiniMax M2 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2 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 |
|---|---|---|
| Maker | Cohere | MiniMax |
| Weights | Open weights | Open weights |
| Released | March 13, 2025 | October 23, 2025 |
| Context window | 256K | 205K |
| Input $/Mtok | $2.50 | $0.255 |
| Output $/Mtok | $10.00 | $1.02 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $2.69 | $0.702 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Command A better than MiniMax M2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Command A has the edge where the context window is larger, 256K against 205K tokens, and where what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, Command A or MiniMax M2?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Per solved SWE-bench Verified task, Command A costs $2.69 and MiniMax M2 $0.702.
Which has the bigger context window, Command A or MiniMax M2?
Command A, with 256K tokens against 205K.
How many benchmarks is the Command A vs MiniMax M2 comparison based on?
37 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's on 1. Where only one model has a result, the page says so instead of naming a winner.