Command A vs DeepSeek V3 0324
Updated October 21, 2026. 26 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 LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 26
- Command A only
- 34
- DeepSeek V3 0324 only
- 9
- 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
Command A
Command A leads, 13.1 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
Command A
Command A leads, 1.0 against 0.8.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V3 0324
DeepSeek V3 0324 leads, 61.6% against 48.5%.
Same board, both measured
Math
AIME
DeepSeek V3 0324
DeepSeek V3 0324 leads, 52.2% against 13.3%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V3 0324
DeepSeek V3 0324 leads, 79.5% against 69.2%.
Same board, both measured
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 0324
Command A $0.0075, DeepSeek V3 0324 $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 0324 not benchmarked.
- Widest category
- Math, 22.6 points apart on average over 5 shared benchmarks.
- Widest single gap
- AIME: Command A 13.3% against DeepSeek V3 0324 52.2%, 38.9 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against DeepSeek V3 0324 $1.07 per million output tokens, 9.3x apart.
- Context window
- Command A takes 256K tokens, DeepSeek V3 0324 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 0324 | Ties |
|---|---|---|---|---|
| Coding | 2 | 3 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 2 | 1 | ||
| Math | 0 | 5 | ||
| Knowledge | 1 | 5 | ||
| General | 2 | 2 | ||
| All shared boards | 10 | 16 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index23
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 42.0% | Only DeepSeek V3 0324 measured |
| AA Coding Index | 27.8 | 21.2 | Command A |
| LiveCodeBench (Vals AI) | 35.1% | 65.5% | DeepSeek V3 0324 |
| 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% | 40.5% | DeepSeek V3 0324 |
| SciCode | 38.5% | 39.0% | DeepSeek V3 0324 |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 15.2% | Command A |
| WeirdML | Not measured | 36.1% | Only DeepSeek V3 0324 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 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 9.7 | Command A |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 0.8 | Command A |
| Finance Agent (Vals AI) | 9.0% | Not measured | Only Command A measured |
| τ²-Bench Telecom | 80.7% | 47.1% | Command A |
| METR time horizons | Not measured | 49.6% | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | 61.6% | DeepSeek V3 0324 |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 65.5% | Command A |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 4.7% | Command A |
| GPQA Diamond (Epoch AI run) | Not measured | 67.6% | Only DeepSeek V3 0324 measured |
| SimpleBench | Not measured | 27.2% | Only DeepSeek V3 0324 measured |
| 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 |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| AIME | 13.3% | 52.2% | DeepSeek V3 0324 |
| MATH 500 (Vals AI) | 76.2% | 88.6% | DeepSeek V3 0324 |
| MGSM (Vals AI) | 85.7% | 91.7% | DeepSeek V3 0324 |
| AA Math Index | 13.0 | 41.0 | DeepSeek V3 0324 |
| AIME 2025 (Artificial Analysis run) | 13.0% | 41.0% | DeepSeek V3 0324 |
| OTIS Mock AIME | Not measured | 37.8% | Only DeepSeek V3 0324 measured |
| MATH level 5 | Not measured | 75.5% | Only DeepSeek V3 0324 measured |
| 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 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| MMLU Pro | 69.2% | 79.5% | DeepSeek V3 0324 |
| LegalBench (Vals AI) | 79.7% | 77.7% | Command A |
| CaseLaw (Vals AI) | 64.5% | Not measured | Only Command A measured |
| CorpFin (Vals AI) | 46.0% | 54.7% | DeepSeek V3 0324 |
| TaxEval (Vals AI) | 61.4% | 71.1% | DeepSeek V3 0324 |
| MedQA (Vals AI) | 80.5% | 82.0% | DeepSeek V3 0324 |
| MedCode (Vals AI) | 19.7% | Not measured | Only Command A measured |
| MMLU Pro (Artificial Analysis run) | 71.2% | 81.9% | DeepSeek V3 0324 |
| 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 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Command A | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | Not measured | Only Command A measured |
| IFBench | 73.9% | 41.0% | Command A |
| Long context reasoning (AA-LCR) | 52.7% | 40.7% | Command A |
| DTBench | 61.3% | 64.8% | DeepSeek V3 0324 |
| LMCA | 10.3% | 15.5% | DeepSeek V3 0324 |
| Fiction.LiveBench | Not measured | 50.0% | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | Not measured | 77.0% | Only DeepSeek V3 0324 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 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | DeepSeek V3 0324 | 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 0324 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3 0324 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3 0324 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 0324 |
|---|---|---|
| Maker | Cohere | DeepSeek |
| Weights | Open weights | Open weights |
| Released | March 13, 2025 | March 24, 2025 |
| Context window | 256K | 164K |
| Input $/Mtok | $2.50 | $0.27 |
| Output $/Mtok | $10.00 | $1.07 |
| 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 0324 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 LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, Command A or DeepSeek V3 0324?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; DeepSeek V3 0324 costs $0.27 and $1.07. Cost per solved task is known for Command A only.
Which has the bigger context window, Command A or DeepSeek V3 0324?
Command A, with 256K tokens against 164K.
How many benchmarks is the Command A vs DeepSeek V3 0324 comparison based on?
26 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 0324's on 0. Where only one model has a result, the page says so instead of naming a winner.