Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs Llama 3-70B
Llama 3-70B has enough public results to be ranked (#323); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 5 shared benchmarks.
DeepSeek
MetaSummary
- They share 5 benchmarks with published results for both. DeepSeek-V2 (MoE-236B, May 2024) scores higher in 1 category and Llama 3-70B 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 35.8.
- The biggest single-benchmark swing is BigCodeBench Instruct: 48.9% for DeepSeek-V2 (MoE-236B, May 2024) and 43.6% for Llama 3-70B.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 40.3 | 28.8 |
| Released | 2024-05-07 | 2024-04-18 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 10 | 31 |
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Category by category
Coding DeepSeek-V2 (MoE-236B, May 2024) leads
DeepSeek-V2 (MoE-236B, May 2024): 40.4 (#139), Llama 3-70B: 35.8 (#218)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| BigCodeBench Instruct | 48.9% | 43.6% |
| BigCodeBench Complete | 59.4% | 54.5% |
| LMArena Coding | — | 1206 |
| HumanEval+ | — | 72% |
| MBPP+ | — | 69% |
Agentic & Tool Use Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 21.1 (#139)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| Cybench | — | 5% |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 18.0 (#288)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| Epoch Capabilities Index | 124.77 | 122.93 |
| WinoGrande | 86.3% | 83.5% |
| Kagi LLM Benchmark | — | 35.1% |
| LMArena Hard Prompts | — | 1195 |
| DTBench | — | 54.2% |
| BIG-Bench Hard | 78.8% | — |
| ForecastBench | — | 57.1 |
| HellaSwag | 87.1% | — |
| PIQA | 83.9% | — |
Math Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 12.8 (#305)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 4.3% |
| LMArena Math | — | 1218 |
| MATH Level 5 | — | 22.6% |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 20.8 (#277)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| MMLU | 78.4% | 79.3% |
| GPQA Diamond | — | 40.6% |
| LMArena Expert | — | 1149 |
| ARC (AI2) Challenge | 92.2% | — |
| TriviaQA | 80% | — |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 33.6 (#251)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| LMArena Non-English | — | 1142 |
| LMArena Chinese | — | 1114 |
| LMArena French | — | 1232 |
| LMArena German | — | 1169 |
| LMArena Japanese | — | 1017 |
| LMArena Korean | — | 1017 |
| LMArena Russian | — | 1159 |
| LMArena Spanish | — | 1241 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 62.5 (#238)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| LMArena Instruction Following | — | 1194 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 35.6 (#240)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| LMArena Longer Query | — | 1174 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama 3-70B: 42.8 (#231)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama 3-70B |
|---|---|---|
| LMArena Text | — | 1221 |
| LMArena Creative Writing | — | 1210 |
| LMArena Multi-Turn | — | 1223 |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than Llama 3-70B?
Llama 3-70B has enough public results to be ranked (#323); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or Llama 3-70B better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 40.4 versus 35.8 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Llama 3-70B share?
5 benchmarks have published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Llama 3-70B has 31.