Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs Llama2 70b Steerlm Chat
Llama2 70b Steerlm Chat has enough public results to be ranked (#265); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
DeepSeek
NVIDIASummary
- The widest gap is in coding, where DeepSeek-V2 (MoE-236B, May 2024) leads 39.8 to 29.3.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat | |
|---|---|---|
| Provider | DeepSeek | NVIDIA |
| Noometry Index | 39.7 | 31.2 |
| Released | 2024-05-07 | — |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 10 | 9 |
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Category by category
Coding DeepSeek-V2 (MoE-236B, May 2024) leads
DeepSeek-V2 (MoE-236B, May 2024): 39.8 (#141), Llama2 70b Steerlm Chat: 29.3 (#295)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | — | 1025 |
| BigCodeBench Complete | 59.4% | — |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama2 70b Steerlm Chat: 19.1 (#245)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Hard Prompts | — | 1047 |
| BIG-Bench Hard | 78.8% | — |
| Epoch Capabilities Index | 124.78 | — |
| HellaSwag | 87.1% | — |
| PIQA | 83.9% | — |
| WinoGrande | 86.3% | — |
Math Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama2 70b Steerlm Chat: 28.8 (#223)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Math | — | 1072 |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama2 70b Steerlm Chat: —
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| ARC (AI2) Challenge | 92.2% | — |
| MMLU | 78.4% | — |
| TriviaQA | 80% | — |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama2 70b Steerlm Chat: 28.9 (#265)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Non-English | — | 1064 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama2 70b Steerlm Chat: 54.5 (#274)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Instruction Following | — | 1061 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama2 70b Steerlm Chat: 30.4 (#283)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Longer Query | — | 998 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Llama2 70b Steerlm Chat: 31.8 (#278)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Text | — | 1098 |
| LMArena Creative Writing | — | 1091 |
| LMArena Multi-Turn | — | 1058 |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than Llama2 70b Steerlm Chat?
Llama2 70b Steerlm Chat has enough public results to be ranked (#265); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or Llama2 70b Steerlm Chat better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 39.8 versus 29.3 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Llama2 70b Steerlm Chat share?
0 benchmarks have published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Llama2 70b Steerlm Chat has 9.