# DeepSeek LLM 67B vs Llama-3.3-70B-Instruct

> Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 24.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-llm-67b-vs-llama-3-3-70b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 3 categories and Llama-3.3-70B-Instruct in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama-3.3-70B-Instruct leads 30.6 to 7.0.
- The biggest single-benchmark swing is MATH Level 5: 6.4% for DeepSeek LLM 67B and 41.6% for Llama-3.3-70B-Instruct.

## Snapshot

| | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 24.9 | 30.6 |
| Rank | 347 | 291 |
| Context | — | 128K |
| Input $/M | — | $0.10 |
| Output $/M | — | $0.32 |
| Weights | Open | Open |

## Coding

- DeepSeek LLM 67B: 31.9 (#278)
- Llama-3.3-70B-Instruct: 31.0 (#290)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Coding | 1096 | 1268 |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |

## Agentic & Tool Use

- DeepSeek LLM 67B: —
- Llama-3.3-70B-Instruct: 25.8 (#105)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |

## Reasoning

- DeepSeek LLM 67B: 16.5 (#304)
- Llama-3.3-70B-Instruct: 14.1 (#327)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1257 |
| Epoch Capabilities Index | 110.5 | 127.33 |
| SimpleBench | — | 19.9% |
| CritPt | — | 0% |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | — | 50.8% |
| DTBench | — | 59.5% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| ForecastBench | — | 58.6 |
| LiveBench | — | 50.2% |

## Math

- DeepSeek LLM 67B: 8.7 (#324)
- Llama-3.3-70B-Instruct: 15.3 (#298)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 5.1% |
| LMArena Math | 1108 | 1267 |
| MATH Level 5 | 6.4% | 41.6% |
| LiveBench Math | — | 42.2% |

## Knowledge

- DeepSeek LLM 67B: 7.0 (#313)
- Llama-3.3-70B-Instruct: 30.6 (#226)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| GPQA Diamond | 24.6% | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| LMArena Expert | — | 1225 |
| MMLU | — | 86.3% |

## Multilingual

- DeepSeek LLM 67B: 29.4 (#267)
- Llama-3.3-70B-Instruct: 39.9 (#220)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1073 | 1236 |
| LMArena Chinese | 1132 | 1217 |
| LMArena French | — | 1281 |
| LMArena German | — | 1251 |
| LMArena Japanese | — | 1150 |
| LMArena Korean | — | 1143 |
| LMArena Russian | — | 1252 |
| LMArena Spanish | — | 1270 |

## Instruction Following

- DeepSeek LLM 67B: 55.4 (#277)
- Llama-3.3-70B-Instruct: 71.1 (#157)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1079 | 1242 |
| LiveBench Instruction Following | — | 82.7% |

## Long Context

- DeepSeek LLM 67B: 33.1 (#265)
- Llama-3.3-70B-Instruct: 26.4 (#295)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1092 | 1256 |
| Fiction.LiveBench | — | 33.3% |

## Writing & Preference

- DeepSeek LLM 67B: 31.6 (#282)
- Llama-3.3-70B-Instruct: 47.6 (#207)

| Benchmark | DeepSeek LLM 67B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1105 | 1274 |
| LMArena Creative Writing | 1067 | 1250 |
| LMArena Multi-Turn | 1082 | 1280 |
| LiveBench Language | — | 39.2% |

## FAQ

### Is DeepSeek LLM 67B better than Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 24.9 on the Noometry Index.

### Is DeepSeek LLM 67B or Llama-3.3-70B-Instruct better for coding?

They score almost the same on coding (31.9 vs 31.0); test both on your own repository before choosing.

### How many benchmarks do DeepSeek LLM 67B and Llama-3.3-70B-Instruct share?

14 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Llama-3.3-70B-Instruct has 43.