Model comparison
DeepSeek LLM 67B vs Qwen1.5-110B
Qwen1.5-110B is the stronger model overall, scoring 34.2 to 24.9 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 10 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and Qwen1.5-110B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen1.5-110B leads 33.7 to 8.7.
Side by side
| DeepSeek LLM 67B | Qwen1.5-110B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 24.9 | 34.2 |
| Released | 2023-11-29 | 2024-04-25 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 15 | 20 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Qwen1.5-110B leads
DeepSeek LLM 67B: 31.9 (#278), Qwen1.5-110B: 33.0 (#264)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| LMArena Coding | 1096 | 1184 |
| BigCodeBench Instruct | — | 35% |
| BigCodeBench Complete | — | 44.4% |
Reasoning Qwen1.5-110B leads
DeepSeek LLM 67B: 16.5 (#304), Qwen1.5-110B: 22.7 (#189)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1168 |
| Chess Puzzles | 0% | — |
| Epoch Capabilities Index | 110.5 | — |
| ForecastBench | — | 57.7 |
Math Qwen1.5-110B leads
DeepSeek LLM 67B: 8.7 (#324), Qwen1.5-110B: 33.7 (#201)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| LMArena Math | 1108 | 1185 |
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| MATH Level 5 | 6.4% | — |
Knowledge Qwen1.5-110B leads
DeepSeek LLM 67B: 7.0 (#313), Qwen1.5-110B: 31.2 (#219)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| LMArena Expert | — | 1144 |
Multilingual Qwen1.5-110B leads
DeepSeek LLM 67B: 29.4 (#267), Qwen1.5-110B: 33.6 (#250)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| LMArena Non-English | 1073 | 1142 |
| LMArena Chinese | 1132 | 1206 |
| LMArena French | — | 1151 |
| LMArena German | — | 1123 |
| LMArena Japanese | — | 1074 |
| LMArena Korean | — | 1044 |
| LMArena Russian | — | 1118 |
| LMArena Spanish | — | 1142 |
Instruction Following Qwen1.5-110B leads
DeepSeek LLM 67B: 55.4 (#277), Qwen1.5-110B: 60.3 (#252)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| LMArena Instruction Following | 1079 | 1158 |
Long Context Qwen1.5-110B leads
DeepSeek LLM 67B: 33.1 (#265), Qwen1.5-110B: 35.1 (#242)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| LMArena Longer Query | 1092 | 1157 |
Writing & Preference Qwen1.5-110B leads
DeepSeek LLM 67B: 31.6 (#282), Qwen1.5-110B: 38.0 (#255)
| Benchmark | DeepSeek LLM 67B | Qwen1.5-110B |
|---|---|---|
| LMArena Text | 1105 | 1175 |
| LMArena Creative Writing | 1067 | 1148 |
| LMArena Multi-Turn | 1082 | 1160 |
Frequently asked questions
Is DeepSeek LLM 67B better than Qwen1.5-110B?
Qwen1.5-110B is the stronger model overall, scoring 34.2 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or Qwen1.5-110B better for coding?
Qwen1.5-110B scores higher on coding benchmarks: 33.0 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and Qwen1.5-110B share?
10 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Qwen1.5-110B has 20.