# Deepseek Coder v2 vs Llama 3-8B

> Deepseek Coder v2 is the stronger model overall, scoring 35.3 to 25.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-coder-v2-vs-llama-3-8b
- Last updated: 2026-10-10
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. Deepseek Coder v2 scores higher in 8 categories and Llama 3-8B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Deepseek Coder v2 leads 32.3 to 8.3.
- The biggest single-benchmark swing is BigCodeBench Complete: 59.7% for Deepseek Coder v2 and 36.9% for Llama 3-8B.

## Snapshot

| | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 35.3 | 25.3 |
| Rank | 217 | 338 |
| Context | — | 8K |
| Input $/M | — | $0.14 |
| Output $/M | — | $0.14 |
| Weights | Open | Open |

## Coding

- Deepseek Coder v2: 37.5 (#178)
- Llama 3-8B: 30.5 (#285)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| BigCodeBench Instruct | 48.2% | 31.9% |
| LMArena Coding | 1251 | 1152 |
| BigCodeBench Complete | 59.7% | 36.9% |
| HumanEval+ | 82.3% | 56.7% |
| MBPP+ | 75.1% | 54.8% |

## Reasoning

- Deepseek Coder v2: 22.6 (#175)
- Llama 3-8B: 13.8 (#321)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| LMArena Hard Prompts | 1207 | 1133 |
| WinoGrande | 83.7% | 75.7% |
| Chess Puzzles | — | 0% |
| DTBench | — | 43.9% |
| Adversarial NLI | — | 57.3% |
| Epoch Capabilities Index | — | 116.33 |
| ForecastBench | — | 58.6 |

## Math

- Deepseek Coder v2: 32.3 (#188)
- Llama 3-8B: 8.3 (#317)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| LMArena Math | 1241 | 1151 |
| OTIS Mock AIME 2024-2025 | — | 1.9% |
| MATH Level 5 | — | 6.1% |
| GSM8K | 94.5% | — |

## Knowledge

- Deepseek Coder v2: 31.7 (#209)
- Llama 3-8B: 7.8 (#303)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| LMArena Expert | 1181 | 1113 |
| ARC (AI2) Challenge | 64.3% | 82.8% |
| GPQA Diamond | — | 26.1% |
| MMLU | — | 68.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |

## Multilingual

- Deepseek Coder v2: 36.4 (#235)
- Llama 3-8B: 31.0 (#256)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| LMArena Non-English | 1182 | 1098 |
| LMArena Chinese | 1201 | 1076 |
| LMArena French | 1184 | 1158 |
| LMArena German | 1164 | 1104 |
| LMArena Japanese | 1126 | 967 |
| LMArena Korean | 1104 | 1003 |
| LMArena Russian | 1188 | 1109 |
| LMArena Spanish | 1153 | 1172 |

## Instruction Following

- Deepseek Coder v2: 61.9 (#237)
- Llama 3-8B: 58.7 (#255)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | 1180 | 1127 |

## Long Context

- Deepseek Coder v2: 37.0 (#219)
- Llama 3-8B: 34.2 (#246)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | 1219 | 1128 |

## Writing & Preference

- Deepseek Coder v2: 38.4 (#249)
- Llama 3-8B: 37.7 (#251)

| Benchmark | Deepseek Coder v2 | Llama 3-8B |
|---|---|---|
| LMArena Text | 1191 | 1166 |
| LMArena Creative Writing | 1120 | 1150 |
| LMArena Multi-Turn | 1176 | 1152 |

## FAQ

### Is Deepseek Coder v2 better than Llama 3-8B?

Deepseek Coder v2 is the stronger model overall, scoring 35.3 to 25.3 on the Noometry Index.

### Is Deepseek Coder v2 or Llama 3-8B better for coding?

Deepseek Coder v2 scores higher on coding benchmarks: 37.5 versus 30.5 in the Noometry coding category.

### How many benchmarks do Deepseek Coder v2 and Llama 3-8B share?

23 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and Llama 3-8B has 34.