# DeepSeek-V3.1-Terminus vs Llama 3-8B

> DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 25.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-llama-3-8b
- Last updated: 2026-10-12
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Llama 3-8B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-V3.1-Terminus leads 38.5 to 8.8.
- The biggest single-benchmark swing is DTBench: 81.3% for DeepSeek-V3.1-Terminus and 43.9% for Llama 3-8B.

## Snapshot

| | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 43.1 | 25.5 |
| Rank | 97 | 344 |
| Context | 164K | — |
| Input $/M | $0.27 | — |
| Output $/M | $1 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1-Terminus: 42.0 (#113)
- Llama 3-8B: 31.0 (#289)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| LMArena Coding | 1426 | 1152 |
| SciCode | 40.6% | — |
| BigCodeBench Instruct | — | 31.9% |
| BigCodeBench Complete | — | 36.9% |
| ALE-Bench | 745.17 | — |
| HumanEval+ | — | 56.7% |
| MBPP+ | — | 54.8% |

## Reasoning

- DeepSeek-V3.1-Terminus: 26.4 (#133)
- Llama 3-8B: 14.3 (#326)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1133 |
| DTBench | 81.3% | 43.9% |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | — | 0% |
| LMCA | 28.6% | — |
| Adversarial NLI | — | 57.3% |
| Epoch Capabilities Index | — | 116.45 |
| ForecastBench | — | 58.6 |
| WinoGrande | — | 75.7% |

## Math

- DeepSeek-V3.1-Terminus: 38.5 (#137)
- Llama 3-8B: 8.8 (#323)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| LMArena Math | 1402 | 1151 |
| OTIS Mock AIME 2024-2025 | — | 1.9% |
| MATH Level 5 | — | 6.1% |

## Knowledge

- DeepSeek-V3.1-Terminus: —
- Llama 3-8B: 7.8 (#308)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| GPQA Diamond | — | 26.1% |
| LMArena Expert | — | 1113 |
| ARC (AI2) Challenge | — | 82.8% |
| MMLU | — | 68.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.1 (#92)
- Llama 3-8B: 30.8 (#261)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| LMArena Non-English | 1407 | 1098 |
| LMArena Russian | 1436 | 1109 |
| LMArena Chinese | — | 1076 |
| LMArena French | — | 1159 |
| LMArena German | — | 1104 |
| LMArena Japanese | — | 967 |
| LMArena Korean | — | 1004 |
| LMArena Spanish | — | 1173 |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.0 (#106)
- Llama 3-8B: 58.4 (#260)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1127 |

## Long Context

- DeepSeek-V3.1-Terminus: 43.4 (#97)
- Llama 3-8B: 34.2 (#251)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | 1421 | 1128 |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.0 (#92)
- Llama 3-8B: 37.5 (#256)

| Benchmark | DeepSeek-V3.1-Terminus | Llama 3-8B |
|---|---|---|
| LMArena Text | 1419 | 1166 |
| LMArena Creative Writing | 1403 | 1150 |
| LMArena Multi-Turn | 1411 | 1152 |

## FAQ

### Is DeepSeek-V3.1-Terminus better than Llama 3-8B?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 25.5 on the Noometry Index.

### Is DeepSeek-V3.1-Terminus or Llama 3-8B better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 31.0 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1-Terminus and Llama 3-8B share?

11 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Llama 3-8B has 34.