# Command A vs DeepSeek-V3.1

> DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 36.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/command-a-vs-deepseek-v3-1
- Last updated: 2026-10-11
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Command A scores higher in 1 category and DeepSeek-V3.1 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V3.1 leads 40.3 to 27.2.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for Command A and 53.2% for DeepSeek-V3.1.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $2.50 / $10 for Command A.
- Command A accepts more context: 256K tokens versus 164K.

## Snapshot

| | Command A | DeepSeek-V3.1 |
|---|---|---|
| Provider | Cohere | DeepSeek |
| Noometry Index | 36.5 | 42.8 |
| Rank | 215 | 108 |
| Context | 256K | 164K |
| Input $/M | $2.50 | $0.25 |
| Output $/M | $10 | $0.95 |
| Weights | Open | Open |

## Coding

- Command A: 27.2 (#322)
- DeepSeek-V3.1: 40.3 (#144)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| LMArena Coding | 1330 | 1417 |
| Aider Polyglot | 12% | — |
| WeirdML | — | 38.4% |

## Agentic & Tool Use

- Command A: 35.9 (#40)
- DeepSeek-V3.1: —

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 57.1% | — |

## Reasoning

- Command A: 18.3 (#283)
- DeepSeek-V3.1: 27.9 (#110)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 53.2% |
| LMArena Hard Prompts | 1326 | 1417 |
| DTBench | 61.3% | 82.7% |
| LMCA | 10.3% | 24.3% |
| SimpleBench | — | 40% |
| Epoch Capabilities Index | — | 139.92 |
| ForecastBench | — | 58 |

## Math

- Command A: 36.2 (#171)
- DeepSeek-V3.1: 38.9 (#122)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| LMArena Math | 1300 | 1420 |

## Knowledge

- Command A: 37.1 (#159)
- DeepSeek-V3.1: 43.7 (#90)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 5.5% |
| LMArena Expert | 1295 | 1405 |

## Multilingual

- Command A: 45.3 (#170)
- DeepSeek-V3.1: 51.6 (#106)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| LMArena Non-English | 1313 | 1400 |
| LMArena Chinese | 1327 | 1469 |
| LMArena French | 1351 | 1447 |
| LMArena German | 1341 | 1411 |
| LMArena Japanese | 1285 | 1378 |
| LMArena Korean | 1285 | 1337 |
| LMArena Russian | 1314 | 1405 |
| LMArena Spanish | 1347 | 1431 |

## Instruction Following

- Command A: 69.1 (#177)
- DeepSeek-V3.1: 73.9 (#110)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| LMArena Instruction Following | 1309 | 1400 |

## Long Context

- Command A: 40.6 (#151)
- DeepSeek-V3.1: 36.3 (#232)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| LMArena Longer Query | 1334 | 1422 |
| Fiction.LiveBench | — | 52.8% |

## Writing & Preference

- Command A: 47.6 (#208)
- DeepSeek-V3.1: 60.3 (#98)

| Benchmark | Command A | DeepSeek-V3.1 |
|---|---|---|
| LMArena Text | 1331 | 1420 |
| LMArena Creative Writing | 1319 | 1401 |
| EQ-Bench Creative Writing | 1145 | 1436 |
| LMArena Multi-Turn | 1339 | 1408 |

## FAQ

### Is Command A better than DeepSeek-V3.1?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 36.5 on the Noometry Index.

### Which is cheaper, Command A or DeepSeek-V3.1?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Command A lists at $2.50 and $10.

### Is Command A or DeepSeek-V3.1 better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 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-V3.1 share?

22 benchmarks have published results for both models. Command A has 24 scored results on Noometry and DeepSeek-V3.1 has 27.