Model comparison
Command A vs DeepSeek-V3
DeepSeek-V3 is the stronger model overall, scoring 39.5 to 36.5 on the Noometry Index.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. Command A scores higher in 2 categories and DeepSeek-V3 in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V3 leads 42.3 to 27.2.
- The biggest single-benchmark swing is Aider Polyglot: 12% for Command A and 55.1% for DeepSeek-V3.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $2.50 / $10 for Command A.
- Command A accepts more context: 256K tokens versus 164K.
Side by side
| Command A | DeepSeek-V3 | |
|---|---|---|
| Provider | Cohere | DeepSeek |
| Noometry Index | 36.5 | 39.5 |
| Released | 2025-03-13 | 2024-12-26 |
| Weights | Open | Open |
| Context window | 256K | 164K |
| Max output | 8K | 164K |
| Input $ / M tokens | $2.50 | $0.24 |
| Output $ / M tokens | $10 | $0.90 |
| Results tracked | 24 | 60 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek-V3 leads
Command A: 27.2 (#322), DeepSeek-V3: 42.3 (#106)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| Aider Polyglot | 12% | 55.1% |
| LMArena Coding | 1330 | 1368 |
| SciCode | — | 35.8% |
| WeirdML | — | 36.1% |
| BigCodeBench Instruct | — | 50% |
| LiveBench Coding | — | 70.9% |
| BigCodeBench Complete | — | 62.2% |
| HumanEval+ | — | 86.6% |
| MBPP+ | — | 73% |
Agentic & Tool Use Not comparable
Command A: 35.9 (#40), DeepSeek-V3: —
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | — |
| METR Time Horizons | — | 49.6% |
Reasoning DeepSeek-V3 leads
Command A: 18.3 (#283), DeepSeek-V3: 20.5 (#236)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 52.3% |
| LMArena Hard Prompts | 1326 | 1365 |
| DTBench | 61.3% | 64.8% |
| LMCA | 10.3% | 15.5% |
| SimpleBench | — | 27.2% |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 65.8% |
| LiveBench Data Analysis | — | 60.9% |
| BIG-Bench Hard | — | 87.5% |
| Epoch Capabilities Index | — | 135.94 |
| ForecastBench | — | 59.1 |
| HellaSwag | — | 88.9% |
| LiveBench | — | 66.9% |
| PIQA | — | 84.7% |
| WinoGrande | — | 85.2% |
Math Command A leads
Command A: 36.2 (#171), DeepSeek-V3: 32.1 (#219)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| LMArena Math | 1300 | 1373 |
| OTIS Mock AIME 2024-2025 | — | 37.8% |
| Omni-MATH | — | 40.3% |
| LiveBench Math | — | 73.5% |
| MATH Level 5 | — | 75.5% |
| FrontierMath (Feb 2025 set) | — | 1.7% |
Knowledge Too close to call
Command A: 37.1 (#159), DeepSeek-V3: 37.5 (#155)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 6.1% |
| LMArena Expert | 1295 | 1351 |
| GPQA Diamond | — | 67.6% |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 26.1% |
| GPQA (HELM) | — | 53.8% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 87.2% |
| TriviaQA | — | 82.9% |
Multilingual DeepSeek-V3 leads
Command A: 45.3 (#170), DeepSeek-V3: 48.5 (#143)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| LMArena Non-English | 1313 | 1358 |
| LMArena Chinese | 1327 | 1391 |
| LMArena French | 1351 | 1385 |
| LMArena German | 1341 | 1374 |
| LMArena Japanese | 1285 | 1333 |
| LMArena Korean | 1285 | 1319 |
| LMArena Russian | 1314 | 1373 |
| LMArena Spanish | 1347 | 1358 |
Instruction Following DeepSeek-V3 leads
Command A: 69.1 (#177), DeepSeek-V3: 72.8 (#130)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| LMArena Instruction Following | 1309 | 1345 |
| LiveBench Instruction Following | — | 81.5% |
| IFEval | — | 83.2% |
Long Context Command A leads
Command A: 40.6 (#151), DeepSeek-V3: 34.0 (#253)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| LMArena Longer Query | 1334 | 1352 |
| Fiction.LiveBench | — | 50% |
Writing & Preference DeepSeek-V3 leads
Command A: 47.6 (#208), DeepSeek-V3: 57.4 (#130)
| Benchmark | Command A | DeepSeek-V3 |
|---|---|---|
| LMArena Text | 1331 | 1375 |
| LMArena Creative Writing | 1319 | 1364 |
| EQ-Bench Creative Writing | 1145 | 1472 |
| LMArena Multi-Turn | 1339 | 1389 |
| Short-Story Creative Writing | — | 77% |
| WildBench | — | 83% |
| LiveBench Language | — | 49.1% |
Frequently asked questions
Is Command A better than DeepSeek-V3?
DeepSeek-V3 is the stronger model overall, scoring 39.5 to 36.5 on the Noometry Index.
Which is cheaper, Command A or DeepSeek-V3?
DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; Command A lists at $2.50 and $10.
Is Command A or DeepSeek-V3 better for coding?
DeepSeek-V3 scores higher on coding benchmarks: 42.3 versus 27.2 in the Noometry coding category.
Which has the bigger context window?
Command A does, with 256K tokens against 164K.
How many benchmarks do Command A and DeepSeek-V3 share?
23 benchmarks have published results for both models. Command A has 24 scored results on Noometry and DeepSeek-V3 has 60.