# Claude 2.1 vs DeepSeek-V3.1

> DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 24.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/claude-2-1-vs-deepseek-v3-1
- Last updated: 2026-10-10
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. Claude 2.1 scores higher in 0 categories and DeepSeek-V3.1 in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.0 to 15.5.
- The biggest single-benchmark swing is DTBench: 51% for Claude 2.1 and 82.7% for DeepSeek-V3.1.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 24.9 | 42.2 |
| Rank | 340 | 106 |
| Context | — | 164K |
| Input $/M | — | $0.25 |
| Output $/M | — | $0.95 |
| Weights | Proprietary | Open |

## Coding

- Claude 2.1: 25.8 (#322)
- DeepSeek-V3.1: 39.8 (#140)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| WeirdML | 7.1% | 38.4% |
| LMArena Coding | — | 1417 |

## Reasoning

- Claude 2.1: 20.6 (#216)
- DeepSeek-V3.1: 27.3 (#109)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| DTBench | 51% | 82.7% |
| Epoch Capabilities Index | 119.22 | 139.92 |
| ForecastBench | 54.2 | 58 |
| SimpleBench | — | 40% |
| Kagi LLM Benchmark | — | 53.2% |
| LMArena Hard Prompts | — | 1417 |
| LMCA | — | 24.3% |

## Math

- Claude 2.1: 9.6 (#309)
- DeepSeek-V3.1: 36.1 (#125)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | — | 1420 |

## Knowledge

- Claude 2.1: 15.5 (#287)
- DeepSeek-V3.1: 43.0 (#86)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| GPQA Diamond | 33% | — |
| Vectara Hallucination Rate | — | 5.5% |
| LMArena Expert | — | 1403 |
| MMLU | 73.5% | — |

## Multilingual

- Claude 2.1: —
- DeepSeek-V3.1: 51.8 (#100)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| LMArena Non-English | — | 1400 |
| LMArena Chinese | — | 1470 |
| LMArena French | — | 1447 |
| LMArena German | — | 1412 |
| LMArena Japanese | — | 1374 |
| LMArena Korean | — | 1337 |
| LMArena Russian | — | 1405 |
| LMArena Spanish | — | 1429 |

## Instruction Following

- Claude 2.1: —
- DeepSeek-V3.1: 74.1 (#105)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| LMArena Instruction Following | — | 1400 |

## Long Context

- Claude 2.1: —
- DeepSeek-V3.1: 36.3 (#227)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| Fiction.LiveBench | — | 52.8% |
| LMArena Longer Query | — | 1422 |

## Writing & Preference

- Claude 2.1: —
- DeepSeek-V3.1: 60.5 (#93)

| Benchmark | Claude 2.1 | DeepSeek-V3.1 |
|---|---|---|
| LMArena Text | — | 1420 |
| LMArena Creative Writing | — | 1401 |
| EQ-Bench Creative Writing | — | 1436 |
| LMArena Multi-Turn | — | 1408 |

## FAQ

### Is Claude 2.1 better than DeepSeek-V3.1?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 24.9 on the Noometry Index.

### Is Claude 2.1 or DeepSeek-V3.1 better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 25.8 in the Noometry coding category.

### How many benchmarks do Claude 2.1 and DeepSeek-V3.1 share?

4 benchmarks have published results for both models. Claude 2.1 has 7 scored results on Noometry and DeepSeek-V3.1 has 27.