# DeepSeek-V2 (MoE-236B, May 2024) vs Llama 2-13B

> Llama 2-13B has enough public results to be ranked (#309); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.

- Canonical page: https://noometry.com/compare/deepseek-v2-vs-llama-2-13b
- Last updated: 2026-10-11
- Shared benchmarks: 8

## Summary

- They share 8 benchmarks with published results for both. DeepSeek-V2 (MoE-236B, May 2024) scores higher in 1 category and Llama 2-13B in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V2 (MoE-236B, May 2024) leads 40.4 to 30.9.

## Snapshot

| | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 40.3 | 29.6 |
| Rank | — | 309 |
| Context | — | — |
| Input $/M | — | — |
| Output $/M | — | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V2 (MoE-236B, May 2024): 40.4 (#139)
- Llama 2-13B: 30.9 (#291)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | — | 1062 |
| BigCodeBench Complete | 59.4% | — |

## Reasoning

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: 12.8 (#337)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| BIG-Bench Hard | 78.8% | 58.2% |
| Epoch Capabilities Index | 124.77 | 106.17 |
| HellaSwag | 87.1% | 80.7% |
| PIQA | 83.9% | 80.8% |
| WinoGrande | 86.3% | 72.8% |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1051 |
| DTBench | — | 42.2% |
| LAMBADA | — | 76.5% |

## Math

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: 31.1 (#229)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| LMArena Math | — | 1065 |
| GSM8K | — | 36.9% |

## Knowledge

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: 28.1 (#249)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| ARC (AI2) Challenge | 92.2% | 60.3% |
| MMLU | 78.4% | 55.6% |
| TriviaQA | 80% | 79.6% |
| LMArena Expert | — | 1030 |
| BoolQ | — | 82.4% |
| OpenBookQA | — | 57% |

## Multimodal

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: —

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| ScienceQA | — | 55.8% |

## Multilingual

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: 26.5 (#279)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| LMArena Non-English | — | 1024 |
| LMArena Chinese | — | 1001 |
| LMArena French | — | 1044 |
| LMArena German | — | 1009 |
| LMArena Japanese | — | 894 |
| LMArena Korean | — | 953 |
| LMArena Russian | — | 1055 |
| LMArena Spanish | — | 1087 |

## Instruction Following

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: 53.3 (#287)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | — | 1045 |

## Long Context

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: 32.3 (#269)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | — | 1064 |

## Writing & Preference

- DeepSeek-V2 (MoE-236B, May 2024): —
- Llama 2-13B: 29.8 (#289)

| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 2-13B |
|---|---|---|
| LMArena Text | — | 1084 |
| LMArena Creative Writing | — | 1047 |
| LMArena Multi-Turn | — | 1050 |

## FAQ

### Is DeepSeek-V2 (MoE-236B, May 2024) better than Llama 2-13B?

Llama 2-13B has enough public results to be ranked (#309); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.

### Is DeepSeek-V2 (MoE-236B, May 2024) or Llama 2-13B better for coding?

DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 40.4 versus 30.9 in the Noometry coding category.

### How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Llama 2-13B share?

8 benchmarks have published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Llama 2-13B has 32.