# Claude 2.1 vs DeepSeek-V2.5 (Sep 2024)

> DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 25.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/claude-2-1-vs-deepseek-v2-5
- Last updated: 2026-10-11
- Shared benchmarks: 0

## Summary

- The widest gap is in math, where DeepSeek-V2.5 (Sep 2024) leads 35.9 to 10.2.
- DeepSeek-V2.5 (Sep 2024) has downloadable open weights; the other is API-only.

## Snapshot

| | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 25.2 | 37.6 |
| Rank | 345 | 200 |
| Context | — | — |
| Input $/M | — | — |
| Output $/M | — | — |
| Weights | Proprietary | Open |

## Coding

- Claude 2.1: 26.2 (#327)
- DeepSeek-V2.5 (Sep 2024): 31.7 (#281)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| Aider Polyglot | — | 17.8% |
| WeirdML | 7.1% | — |
| BigCodeBench Instruct | — | 48.6% |
| LMArena Coding | — | 1309 |
| BigCodeBench Complete | — | 53.2% |
| HumanEval+ | — | 83.5% |
| MBPP+ | — | 74.1% |

## Reasoning

- Claude 2.1: 21.4 (#221)
- DeepSeek-V2.5 (Sep 2024): 25.6 (#145)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| LMArena Hard Prompts | — | 1289 |
| DTBench | 51% | — |
| Epoch Capabilities Index | 119.27 | — |
| ForecastBench | 54.2 | — |

## Math

- Claude 2.1: 10.2 (#315)
- DeepSeek-V2.5 (Sep 2024): 35.9 (#177)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | — | 1288 |

## Knowledge

- Claude 2.1: 15.4 (#292)
- DeepSeek-V2.5 (Sep 2024): 34.8 (#193)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| GPQA Diamond | 33% | — |
| LMArena Expert | — | 1266 |
| MMLU | 73.5% | — |

## Multilingual

- Claude 2.1: —
- DeepSeek-V2.5 (Sep 2024): 42.5 (#193)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| LMArena Non-English | — | 1273 |
| LMArena Chinese | — | 1318 |
| LMArena French | — | 1289 |
| LMArena German | — | 1258 |
| LMArena Japanese | — | 1228 |
| LMArena Korean | — | 1209 |
| LMArena Russian | — | 1289 |
| LMArena Spanish | — | 1248 |

## Instruction Following

- Claude 2.1: —
- DeepSeek-V2.5 (Sep 2024): 67.5 (#194)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| LMArena Instruction Following | — | 1280 |

## Long Context

- Claude 2.1: —
- DeepSeek-V2.5 (Sep 2024): 39.5 (#174)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| LMArena Longer Query | — | 1301 |

## Writing & Preference

- Claude 2.1: —
- DeepSeek-V2.5 (Sep 2024): 49.8 (#187)

| Benchmark | Claude 2.1 | DeepSeek-V2.5 (Sep 2024) |
|---|---|---|
| LMArena Text | — | 1294 |
| LMArena Creative Writing | — | 1285 |
| LMArena Multi-Turn | — | 1297 |

## FAQ

### Is Claude 2.1 better than DeepSeek-V2.5 (Sep 2024)?

DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 25.2 on the Noometry Index.

### Is Claude 2.1 or DeepSeek-V2.5 (Sep 2024) better for coding?

DeepSeek-V2.5 (Sep 2024) scores higher on coding benchmarks: 31.7 versus 26.2 in the Noometry coding category.

### How many benchmarks do Claude 2.1 and DeepSeek-V2.5 (Sep 2024) share?

0 benchmarks have published results for both models. Claude 2.1 has 7 scored results on Noometry and DeepSeek-V2.5 (Sep 2024) has 22.