Model comparison
DeepSeek LLM 67B vs Qwen2.5-Coder (1.5B)
DeepSeek LLM 67B has enough public results to be ranked (#347); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 1 benchmark with published results for both.
Side by side
| DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 24.9 | — |
| Released | 2023-11-29 | 2024-09-18 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 15 | 6 |
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Category by category
Coding Not comparable
DeepSeek LLM 67B: 31.9 (#278), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Coding | 1096 | — |
Reasoning Not comparable
DeepSeek LLM 67B: 16.5 (#304), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| Epoch Capabilities Index | 110.5 | 113.14 |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1070 | — |
| HellaSwag | — | 76.8% |
| WinoGrande | — | 72.9% |
Math Not comparable
DeepSeek LLM 67B: 8.7 (#324), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| LMArena Math | 1108 | — |
| MATH Level 5 | 6.4% | — |
| GSM8K | — | 86.7% |
Knowledge Not comparable
DeepSeek LLM 67B: 7.0 (#313), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| ARC (AI2) Challenge | — | 60.9% |
| MMLU | — | 68% |
Multilingual Not comparable
DeepSeek LLM 67B: 29.4 (#267), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Non-English | 1073 | — |
| LMArena Chinese | 1132 | — |
Instruction Following Not comparable
DeepSeek LLM 67B: 55.4 (#277), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Instruction Following | 1079 | — |
Long Context Not comparable
DeepSeek LLM 67B: 33.1 (#265), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Longer Query | 1092 | — |
Writing & Preference Not comparable
DeepSeek LLM 67B: 31.6 (#282), Qwen2.5-Coder (1.5B): —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Text | 1105 | — |
| LMArena Creative Writing | 1067 | — |
| LMArena Multi-Turn | 1082 | — |
Frequently asked questions
Is DeepSeek LLM 67B better than Qwen2.5-Coder (1.5B)?
DeepSeek LLM 67B has enough public results to be ranked (#347); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.
How many benchmarks do DeepSeek LLM 67B and Qwen2.5-Coder (1.5B) share?
1 benchmark has published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Qwen2.5-Coder (1.5B) has 6.