# Deepseek Coder v2 vs Llama 3.1-8B

> Deepseek Coder v2 is the stronger model overall, scoring 35.9 to 23.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-coder-v2-vs-llama-3-1-8b
- Last updated: 2026-10-11
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Deepseek Coder v2 scores higher in 8 categories and Llama 3.1-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Deepseek Coder v2 leads 34.9 to 10.2.
- The biggest single-benchmark swing is BigCodeBench Complete: 59.7% for Deepseek Coder v2 and 40.5% for Llama 3.1-8B.

## Snapshot

| | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 35.9 | 23.0 |
| Rank | 220 | 352 |
| Context | — | 128K |
| Input $/M | — | $0.05 |
| Output $/M | — | $0.08 |
| Weights | Open | Open |

## Coding

- Deepseek Coder v2: 38.1 (#183)
- Llama 3.1-8B: 20.2 (#340)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| BigCodeBench Instruct | 48.2% | 32.8% |
| LMArena Coding | 1251 | 1195 |
| BigCodeBench Complete | 59.7% | 40.5% |
| HumanEval+ | 82.3% | 62.8% |
| MBPP+ | 75.1% | 55.6% |
| SciCode | — | 13.2% |
| WeirdML | — | 1.7% |

## Agentic & Tool Use

- Deepseek Coder v2: —
- Llama 3.1-8B: 22.5 (#131)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |

## Reasoning

- Deepseek Coder v2: 23.6 (#176)
- Llama 3.1-8B: 14.9 (#321)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| LMArena Hard Prompts | 1207 | 1175 |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Epoch Capabilities Index | — | 116.57 |
| PIQA | — | 81.2% |
| WinoGrande | 83.7% | — |

## Math

- Deepseek Coder v2: 34.9 (#190)
- Llama 3.1-8B: 10.2 (#317)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| LMArena Math | 1241 | 1179 |
| GSM8K | 94.5% | 82.4% |
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| Omni-MATH | — | 13.7% |
| MATH Level 5 | — | 22.9% |

## Knowledge

- Deepseek Coder v2: 32.3 (#212)
- Llama 3.1-8B: 8.0 (#307)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| LMArena Expert | 1181 | 1144 |
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| ARC (AI2) Challenge | 64.3% | — |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |

## Multilingual

- Deepseek Coder v2: 36.3 (#240)
- Llama 3.1-8B: 34.0 (#249)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | 1182 | 1148 |
| LMArena Chinese | 1201 | 1151 |
| LMArena French | 1185 | 1177 |
| LMArena German | 1164 | 1144 |
| LMArena Japanese | 1126 | 1061 |
| LMArena Korean | 1104 | 1053 |
| LMArena Russian | 1188 | 1158 |
| LMArena Spanish | 1153 | 1169 |

## Instruction Following

- Deepseek Coder v2: 61.7 (#242)
- Llama 3.1-8B: 58.9 (#258)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| LMArena Instruction Following | 1180 | 1159 |
| IFEval | — | 74.3% |

## Long Context

- Deepseek Coder v2: 37.0 (#224)
- Llama 3.1-8B: 35.8 (#238)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | 1219 | 1182 |

## Writing & Preference

- Deepseek Coder v2: 38.2 (#253)
- Llama 3.1-8B: 29.7 (#290)

| Benchmark | Deepseek Coder v2 | Llama 3.1-8B |
|---|---|---|
| LMArena Text | 1191 | 1187 |
| LMArena Creative Writing | 1120 | 1154 |
| LMArena Multi-Turn | 1177 | 1172 |
| EQ-Bench Creative Writing | — | 713 |
| WildBench | — | 68.7% |

## FAQ

### Is Deepseek Coder v2 better than Llama 3.1-8B?

Deepseek Coder v2 is the stronger model overall, scoring 35.9 to 23.0 on the Noometry Index.

### Is Deepseek Coder v2 or Llama 3.1-8B better for coding?

Deepseek Coder v2 scores higher on coding benchmarks: 38.1 versus 20.2 in the Noometry coding category.

### How many benchmarks do Deepseek Coder v2 and Llama 3.1-8B share?

22 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and Llama 3.1-8B has 43.