Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs Qwen2.5-Coder-32B
Qwen2.5-Coder-32B has enough public results to be ranked (#239); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 7 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. DeepSeek-V2 (MoE-236B, May 2024) scores higher in 1 category and Qwen2.5-Coder-32B 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 22.4.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 39.7 | 32.9 |
| Released | 2024-05-07 | 2024-09-18 |
| Weights | Open | Open |
| Context window | — | 33K |
| Max output | — | 29K |
| Input $ / M tokens | — | $0.66 |
| Output $ / M tokens | — | $1 |
| 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): 39.8 (#141), Qwen2.5-Coder-32B: 22.4 (#328)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| BigCodeBench Instruct | 48.9% | 49% |
| BigCodeBench Complete | 59.4% | 58% |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| LiveBench Coding | — | 56.9% |
| LMArena Coding | — | 1276 |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen2.5-Coder-32B: 20.4 (#220)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| Epoch Capabilities Index | 124.78 | 119.41 |
| HellaSwag | 87.1% | 83% |
| WinoGrande | 86.3% | 80.8% |
| LiveBench Reasoning | — | 42.1% |
| LMArena Hard Prompts | — | 1251 |
| LiveBench Data Analysis | — | 49.9% |
| BIG-Bench Hard | 78.8% | — |
| LiveBench | — | 46.2% |
| PIQA | 83.9% | — |
Math Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen2.5-Coder-32B: 30.8 (#203)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Math | — | 46.6% |
| LMArena Math | — | 1251 |
| GSM8K | — | 93% |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen2.5-Coder-32B: 32.9 (#200)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| ARC (AI2) Challenge | 92.2% | 70.5% |
| MMLU | 78.4% | 79.1% |
| LMArena Expert | — | 1221 |
| TriviaQA | 80% | — |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen2.5-Coder-32B: 38.0 (#230)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | — | 1205 |
| LMArena Chinese | — | 1222 |
| LMArena Russian | — | 1228 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen2.5-Coder-32B: 61.6 (#240)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Instruction Following | — | 58.7% |
| LMArena Instruction Following | — | 1223 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen2.5-Coder-32B: 37.9 (#204)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | — | 1251 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Qwen2.5-Coder-32B: 41.8 (#235)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | — | 1230 |
| LMArena Creative Writing | — | 1174 |
| LMArena Multi-Turn | — | 1222 |
| LiveBench Language | — | 23.3% |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than Qwen2.5-Coder-32B?
Qwen2.5-Coder-32B has enough public results to be ranked (#239); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or Qwen2.5-Coder-32B better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 39.8 versus 22.4 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Qwen2.5-Coder-32B share?
7 benchmarks have published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Qwen2.5-Coder-32B has 31.