# DeepSeek-V2.5 (Sep 2024) vs Llama 2-7B

> DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 29.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-llama-2-7b
- Last updated: 2026-10-11
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 8 categories and Llama 2-7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V2.5 (Sep 2024) leads 49.8 to 28.0.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 37.6 | 29.1 |
| Rank | 200 | 317 |
| Context | — | — |
| Input $/M | — | — |
| Output $/M | — | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.7 (#281)
- Llama 2-7B: 29.2 (#307)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Coding | 1309 | 1002 |
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |

## Reasoning

- DeepSeek-V2.5 (Sep 2024): 25.6 (#145)
- Llama 2-7B: 15.7 (#312)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1009 |
| Chess Puzzles | — | 0% |
| BIG-Bench Hard | — | 39.2% |
| Epoch Capabilities Index | — | 99.06 |
| HellaSwag | — | 77.2% |
| LAMBADA | — | 73.3% |
| PIQA | — | 78.8% |
| WinoGrande | — | 69.2% |

## Math

- DeepSeek-V2.5 (Sep 2024): 35.9 (#177)
- Llama 2-7B: 30.7 (#233)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Math | 1288 | 1042 |
| GSM8K | — | 16.7% |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.8 (#193)
- Llama 2-7B: 28.2 (#248)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Expert | 1266 | 1036 |
| ARC (AI2) Challenge | — | 45.9% |
| BoolQ | — | 77.9% |
| MMLU | — | 45.8% |
| OpenBookQA | — | 58.6% |
| TriviaQA | — | 73.7% |

## Multimodal

- DeepSeek-V2.5 (Sep 2024): —
- Llama 2-7B: —

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| ScienceQA | — | 43.1% |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.5 (#193)
- Llama 2-7B: 23.8 (#293)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Non-English | 1273 | 973 |
| LMArena Chinese | 1318 | 973 |
| LMArena French | 1289 | 970 |
| LMArena German | 1258 | 978 |
| LMArena Russian | 1289 | 995 |
| LMArena Spanish | 1248 | 1007 |
| LMArena Japanese | 1228 | — |
| LMArena Korean | 1209 | — |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.5 (#194)
- Llama 2-7B: 50.8 (#298)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Instruction Following | 1280 | 1006 |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#174)
- Llama 2-7B: 30.4 (#287)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Longer Query | 1301 | 999 |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 49.8 (#187)
- Llama 2-7B: 28.0 (#298)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-7B |
|---|---|---|
| LMArena Text | 1294 | 1053 |
| LMArena Creative Writing | 1285 | 1033 |
| LMArena Multi-Turn | 1297 | 1029 |

## FAQ

### Is DeepSeek-V2.5 (Sep 2024) better than Llama 2-7B?

DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 29.1 on the Noometry Index.

### Is DeepSeek-V2.5 (Sep 2024) or Llama 2-7B better for coding?

DeepSeek-V2.5 (Sep 2024) scores higher on coding benchmarks: 31.7 versus 29.2 in the Noometry coding category.

### How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Llama 2-7B share?

15 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Llama 2-7B has 29.