Command A vs DeepSeek V3.1 Terminus
Updated October 21, 2026. 36 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 164K tokens, and where what matters is AA Coding Index or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 36
- Command A only
- 24
- DeepSeek V3.1 Terminus only
- 8
- 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
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus leads, 14.8 against 13.1.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus leads, 6.8 against 1.0.
Same board, both measured
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 DeepSeek V3.1 Terminus has a Design Arena: websites result, 1187.
Directional only
Long documents
Listed context window
Command A
Command A takes 256K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1 Terminus
Command A $0.0075, DeepSeek V3.1 Terminus $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Command A has the number, $2.69.
Directional only
At a glance
- Coding index
- Command A not benchmarked, DeepSeek V3.1 Terminus not benchmarked.
- Widest category
- Math, 56.8 points apart on average over 3 shared benchmarks.
- Widest single gap
- AA Math Index: Command A 13.0 against DeepSeek V3.1 Terminus 89.7, 76.7 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against DeepSeek V3.1 Terminus $1.0142 per million output tokens, 9.9x apart.
- Context window
- Command A takes 256K tokens, DeepSeek V3.1 Terminus 164K.
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 | DeepSeek V3.1 Terminus | Ties |
|---|---|---|---|---|
| Coding | 1 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 5 | ||
| General | 1 | 14 | ||
| All shared boards | 3 | 33 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index15
| Benchmark | Command A | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| AA Coding Index | 27.8 | 43.5 | DeepSeek V3.1 Terminus |
| 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% | 79.8% | DeepSeek V3.1 Terminus |
| SciCode | 38.5% | 38.0% | Command A |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 31.8% | DeepSeek V3.1 Terminus |
| ALE-Bench | Not measured | 745.2 | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: coding | 1330 | 1425 | DeepSeek V3.1 Terminus |
| LMArena Text: software and IT | 1336 | 1426 | DeepSeek V3.1 Terminus |
| 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 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 14.8 | DeepSeek V3.1 Terminus |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Command A | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 6.8 | DeepSeek V3.1 Terminus |
| Finance Agent (Vals AI) | 9.0% | Not measured | Only Command A measured |
| τ²-Bench Telecom | 80.7% | 37.1% | Command A |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Command A | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | Not measured | Only Command A measured |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 79.2% | DeepSeek V3.1 Terminus |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 16.4% | DeepSeek V3.1 Terminus |
| LMArena Text: hard prompts | 1326 | 1426 | DeepSeek V3.1 Terminus |
| LMArena Text: expert | 1296 | Not measured | Only Command A measured |
| LMArena Text: hard prompts in English | 1335 | 1432 | DeepSeek V3.1 Terminus |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Command A | DeepSeek V3.1 Terminus | 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 | 89.7 | DeepSeek V3.1 Terminus |
| AIME 2025 (Artificial Analysis run) | 13.0% | 89.7% | DeepSeek V3.1 Terminus |
| LMArena Text: math | 1300 | 1402 | DeepSeek V3.1 Terminus |
| 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 index05
| Benchmark | Command A | DeepSeek V3.1 Terminus | 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% | 85.1% | DeepSeek V3.1 Terminus |
| LMArena Text: science | 1339 | 1451 | DeepSeek V3.1 Terminus |
| LMArena Text: medicine and healthcare | 1334 | 1468 | DeepSeek V3.1 Terminus |
| LMArena Text: legal and government | 1348 | 1457 | DeepSeek V3.1 Terminus |
| LMArena Text: business and finance | 1315 | 1414 | DeepSeek V3.1 Terminus |
| 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 | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1187 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: UI components | Not measured | 1182 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: game dev | Not measured | 1131 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: data viz | Not measured | 1167 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: 3D | Not measured | 1141 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: all code categories | Not measured | 1175 | Only DeepSeek V3.1 Terminus measured |
| Design Arena: SVG | Not measured | 1065 | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index114
| Benchmark | Command A | DeepSeek V3.1 Terminus | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | Not measured | Only Command A measured |
| IFBench | 73.9% | 57.0% | Command A |
| Long context reasoning (AA-LCR) | 52.7% | 69.3% | DeepSeek V3.1 Terminus |
| DTBench | 61.3% | 81.3% | DeepSeek V3.1 Terminus |
| LMCA | 10.3% | 28.6% | DeepSeek V3.1 Terminus |
| LMArena Text | 1331 | 1419 | DeepSeek V3.1 Terminus |
| LMArena Text: instruction following | 1309 | 1404 | DeepSeek V3.1 Terminus |
| LMArena Text: creative writing | 1319 | 1403 | DeepSeek V3.1 Terminus |
| LMArena Text: English | 1344 | 1429 | DeepSeek V3.1 Terminus |
| LMArena Text: non-English | 1313 | 1408 | DeepSeek V3.1 Terminus |
| 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 | 1435 | DeepSeek V3.1 Terminus |
| LMArena Text: Polish | 1324 | 1427 | DeepSeek V3.1 Terminus |
| LMArena Text: multi-turn | 1338 | 1411 | DeepSeek V3.1 Terminus |
| LMArena Text: longer queries | 1334 | 1422 | DeepSeek V3.1 Terminus |
| LMArena Text: writing and language | 1328 | 1409 | DeepSeek V3.1 Terminus |
| LMArena Text: entertainment and media | 1306 | 1391 | DeepSeek V3.1 Terminus |
| 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 | DeepSeek V3.1 Terminus | 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
DeepSeek V3.1 Terminus costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 Terminus costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 Terminus 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 | DeepSeek V3.1 Terminus |
|---|---|---|
| Maker | Cohere | DeepSeek |
| Weights | Open weights | Open weights |
| Released | March 13, 2025 | September 22, 2025 |
| Context window | 256K | 164K |
| Input $/Mtok | $2.50 | $0.3063 |
| Output $/Mtok | $10.00 | $1.0142 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $2.69 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Command A better than DeepSeek V3.1 Terminus 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 164K tokens, and where what matters is AA Coding Index or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, Command A or DeepSeek V3.1 Terminus?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; DeepSeek V3.1 Terminus costs $0.3063 and $1.0142. Cost per solved task is known for Command A only.
Which has the bigger context window, Command A or DeepSeek V3.1 Terminus?
Command A, with 256K tokens against 164K.
How many benchmarks is the Command A vs DeepSeek V3.1 Terminus comparison based on?
36 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and DeepSeek V3.1 Terminus's on 0. Where only one model has a result, the page says so instead of naming a winner.