# Command R+ vs DeepSeek-V3

> DeepSeek-V3 is the stronger model overall, scoring 39.2 to 32.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/command-r-plus-vs-deepseek-v3
- Last updated: 2026-10-10
- Shared benchmarks: 34

## Summary

- They share 34 benchmarks with published results for both. Command R+ scores higher in 1 category and DeepSeek-V3 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3 leads 57.6 to 43.7.
- The biggest single-benchmark swing is LiveBench Math: 21.3% for Command R+ and 73.5% for DeepSeek-V3.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $2.50 / $10 for Command R+.
- DeepSeek-V3 accepts more context: 164K tokens versus 128K.

## Snapshot

| | Command R+ | DeepSeek-V3 |
|---|---|---|
| Provider | Cohere | DeepSeek |
| Noometry Index | 32.0 | 39.2 |
| Rank | 251 | 157 |
| Context | 128K | 164K |
| Input $/M | $2.50 | $0.24 |
| Output $/M | $10 | $0.90 |
| Weights | Open | Open |

## Coding

- Command R+: 28.6 (#304)
- DeepSeek-V3: 41.9 (#99)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| BigCodeBench Instruct | 33.8% | 50% |
| LiveBench Coding | 19.1% | 70.9% |
| LMArena Coding | 1187 | 1368 |
| BigCodeBench Complete | 41.9% | 62.2% |
| HumanEval+ | 56.7% | 86.6% |
| MBPP+ | 63.5% | 73% |
| Aider Polyglot | — | 55.1% |
| SciCode | — | 35.8% |
| WeirdML | — | 36.1% |

## Agentic & Tool Use

- Command R+: —
- DeepSeek-V3: —

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| METR Time Horizons | — | 49.6% |

## Reasoning

- Command R+: 8.9 (#341)
- DeepSeek-V3: 20.0 (#226)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| SimpleBench | 17.4% | 27.2% |
| LiveBench Reasoning | 24.8% | 65.8% |
| LMArena Hard Prompts | 1186 | 1365 |
| DTBench | 54.9% | 64.8% |
| LiveBench Data Analysis | 38.1% | 60.9% |
| LMCA | 5% | 15.5% |
| Epoch Capabilities Index | 119.28 | 135.95 |
| LiveBench | 31.8% | 66.9% |
| Kagi LLM Benchmark | — | 52.3% |
| CritPt | — | 0% |
| BIG-Bench Hard | — | 87.5% |
| ForecastBench | — | 59.1 |
| HellaSwag | — | 88.9% |
| PIQA | — | 84.7% |
| WinoGrande | — | 85.2% |

## Math

- Command R+: 26.6 (#239)
- DeepSeek-V3: 30.4 (#208)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| LiveBench Math | 21.3% | 73.5% |
| LMArena Math | 1188 | 1373 |
| OTIS Mock AIME 2024-2025 | — | 37.8% |
| Omni-MATH | — | 40.3% |
| MATH Level 5 | — | 75.5% |
| FrontierMath (Feb 2025 set) | — | 1.7% |

## Knowledge

- Command R+: 35.9 (#165)
- DeepSeek-V3: 37.5 (#147)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| Vectara Hallucination Rate | 6.9% | 6.1% |
| LMArena Expert | 1174 | 1352 |
| MMLU | 69.4% | 87.2% |
| GPQA Diamond | — | 67.6% |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 26.1% |
| GPQA (HELM) | — | 53.8% |
| ARC (AI2) Challenge | — | 95.3% |
| TriviaQA | — | 82.9% |

## Multilingual

- Command R+: 38.8 (#222)
- DeepSeek-V3: 48.8 (#138)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| LMArena Non-English | 1216 | 1358 |
| LMArena Chinese | 1226 | 1390 |
| LMArena French | 1208 | 1386 |
| LMArena German | 1216 | 1374 |
| LMArena Japanese | 1166 | 1333 |
| LMArena Korean | 1138 | 1321 |
| LMArena Russian | 1227 | 1372 |
| LMArena Spanish | 1189 | 1358 |

## Instruction Following

- Command R+: 60.2 (#249)
- DeepSeek-V3: 73.0 (#125)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| LiveBench Instruction Following | 57.6% | 81.5% |
| LMArena Instruction Following | 1197 | 1345 |
| IFEval | — | 83.2% |

## Long Context

- Command R+: 37.3 (#214)
- DeepSeek-V3: 34.0 (#248)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| LMArena Longer Query | 1231 | 1353 |
| Fiction.LiveBench | — | 50% |

## Writing & Preference

- Command R+: 43.7 (#223)
- DeepSeek-V3: 57.6 (#124)

| Benchmark | Command R+ | DeepSeek-V3 |
|---|---|---|
| LMArena Text | 1229 | 1375 |
| LMArena Creative Writing | 1235 | 1364 |
| LMArena Multi-Turn | 1213 | 1389 |
| LiveBench Language | 29.7% | 49.1% |
| Short-Story Creative Writing | — | 77% |
| EQ-Bench Creative Writing | — | 1472 |
| WildBench | — | 83% |

## FAQ

### Is Command R+ better than DeepSeek-V3?

DeepSeek-V3 is the stronger model overall, scoring 39.2 to 32.0 on the Noometry Index.

### Which is cheaper, Command R+ or DeepSeek-V3?

DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; Command R+ lists at $2.50 and $10.

### Is Command R+ or DeepSeek-V3 better for coding?

DeepSeek-V3 scores higher on coding benchmarks: 41.9 versus 28.6 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3 does, with 164K tokens against 128K.

### How many benchmarks do Command R+ and DeepSeek-V3 share?

34 benchmarks have published results for both models. Command R+ has 34 scored results on Noometry and DeepSeek-V3 has 60.