# DeepSeek-V2.5 (Sep 2024) vs Llama 2-13B

> DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 29.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-llama-2-13b
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 8 categories and Llama 2-13B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V2.5 (Sep 2024) leads 49.8 to 29.8.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 37.6 | 29.6 |
| Rank | 200 | 309 |
| Context | — | — |
| Input $/M | — | — |
| Output $/M | — | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.7 (#281)
- Llama 2-13B: 30.9 (#291)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1309 | 1062 |
| 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 2-13B: 12.8 (#337)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1051 |
| Chess Puzzles | — | 0% |
| DTBench | — | 42.2% |
| BIG-Bench Hard | — | 58.2% |
| Epoch Capabilities Index | — | 106.17 |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |

## Math

- DeepSeek-V2.5 (Sep 2024): 35.9 (#177)
- Llama 2-13B: 31.1 (#229)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Math | 1288 | 1065 |
| GSM8K | — | 36.9% |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.8 (#193)
- Llama 2-13B: 28.1 (#249)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1266 | 1030 |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |

## Multimodal

- DeepSeek-V2.5 (Sep 2024): —
- Llama 2-13B: —

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| ScienceQA | — | 55.8% |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.5 (#193)
- Llama 2-13B: 26.5 (#279)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1273 | 1024 |
| LMArena Chinese | 1318 | 1001 |
| LMArena French | 1289 | 1044 |
| LMArena German | 1258 | 1009 |
| LMArena Japanese | 1228 | 894 |
| LMArena Korean | 1209 | 953 |
| LMArena Russian | 1289 | 1055 |
| LMArena Spanish | 1248 | 1087 |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.5 (#194)
- Llama 2-13B: 53.3 (#287)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1280 | 1045 |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#174)
- Llama 2-13B: 32.3 (#269)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1301 | 1064 |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 49.8 (#187)
- Llama 2-13B: 29.8 (#289)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Llama 2-13B |
|---|---|---|
| LMArena Text | 1294 | 1084 |
| LMArena Creative Writing | 1285 | 1047 |
| LMArena Multi-Turn | 1297 | 1050 |

## FAQ

### Is DeepSeek-V2.5 (Sep 2024) better than Llama 2-13B?

DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 29.6 on the Noometry Index.

### Is DeepSeek-V2.5 (Sep 2024) or Llama 2-13B better for coding?

They score almost the same on coding (31.7 vs 30.9); test both on your own repository before choosing.

### How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Llama 2-13B share?

17 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Llama 2-13B has 32.