Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs Qwen1.5-72B
Qwen1.5-72B has enough public results to be ranked (#282); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 2 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. DeepSeek-V2 (MoE-236B, May 2024) scores higher in 1 category and Qwen1.5-72B in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V2 (MoE-236B, May 2024) leads 39.8 to 31.4.
- The biggest single-benchmark swing is BigCodeBench Complete: 59.4% for DeepSeek-V2 (MoE-236B, May 2024) and 40.3% for Qwen1.5-72B.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 39.7 | 30.3 |
| Released | 2024-05-07 | 2024-02-04 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 10 | 22 |
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Category by category
Coding DeepSeek-V2 (MoE-236B, May 2024) leads
DeepSeek-V2 (MoE-236B, May 2024): 39.8 (#141), Qwen1.5-72B: 31.4 (#272)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| BigCodeBench Instruct | 48.9% | 33.2% |
| BigCodeBench Complete | 59.4% | 40.3% |
| LMArena Coding | — | 1166 |
| HumanEval+ | — | 59.1% |
| MBPP+ | — | 61.6% |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen1.5-72B: 21.2 (#201)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| LMArena Hard Prompts | — | 1148 |
| 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): —, Qwen1.5-72B: 30.7 (#205)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| LMArena Math | — | 1164 |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen1.5-72B: 11.5 (#295)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| GPQA Diamond | — | 28.8% |
| LMArena Expert | — | 1136 |
| ARC (AI2) Challenge | 92.2% | — |
| MMLU | 78.4% | — |
| TriviaQA | 80% | — |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen1.5-72B: 33.4 (#248)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| LMArena Non-English | — | 1135 |
| LMArena Chinese | — | 1186 |
| LMArena French | — | 1158 |
| LMArena German | — | 1084 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1049 |
| LMArena Russian | — | 1104 |
| LMArena Spanish | — | 1110 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen1.5-72B: 59.6 (#251)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| LMArena Instruction Following | — | 1142 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen1.5-72B: 35.0 (#238)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| LMArena Longer Query | — | 1157 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen1.5-72B: 37.4 (#253)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen1.5-72B |
|---|---|---|
| LMArena Text | — | 1166 |
| LMArena Creative Writing | — | 1137 |
| LMArena Multi-Turn | — | 1160 |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than Qwen1.5-72B?
Qwen1.5-72B has enough public results to be ranked (#282); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or Qwen1.5-72B better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 39.8 versus 31.4 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Qwen1.5-72B share?
2 benchmarks have published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Qwen1.5-72B has 22.