Model comparison
DeepSeek LLM 67B vs Qwen-14B
Qwen-14B is the stronger model overall, scoring 31.4 to 24.9 on the Noometry Index.
Last verified . 11 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 11 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 5 categories and Qwen-14B in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen-14B leads 31.2 to 8.7.
Side by side
| DeepSeek LLM 67B | Qwen-14B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 24.9 | 31.4 |
| Released | 2023-11-29 | 2023-09-24 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 15 | 18 |
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Category by category
Coding Too close to call
DeepSeek LLM 67B: 31.9 (#278), Qwen-14B: 31.2 (#288)
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| LMArena Coding | 1096 | 1071 |
Reasoning Qwen-14B leads
DeepSeek LLM 67B: 16.5 (#304), Qwen-14B: 19.6 (#257)
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1027 |
| Epoch Capabilities Index | 110.5 | 113.03 |
| Chess Puzzles | 0% | — |
| BIG-Bench Hard | — | 55% |
| LAMBADA | — | 71.1% |
| PIQA | — | 79.9% |
Math Qwen-14B leads
DeepSeek LLM 67B: 8.7 (#324), Qwen-14B: 31.2 (#227)
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| LMArena Math | 1108 | 1068 |
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| MATH Level 5 | 6.4% | — |
| GSM8K | — | 61.3% |
Knowledge Not comparable
DeepSeek LLM 67B: 7.0 (#313), Qwen-14B: —
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| ARC (AI2) Challenge | — | 84.4% |
| BoolQ | — | 86.2% |
| MMLU | — | 66.3% |
Multilingual DeepSeek LLM 67B leads
DeepSeek LLM 67B: 29.4 (#267), Qwen-14B: 27.5 (#275)
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| LMArena Non-English | 1073 | 1041 |
| LMArena Chinese | 1132 | 1077 |
Instruction Following DeepSeek LLM 67B leads
DeepSeek LLM 67B: 55.4 (#277), Qwen-14B: 52.4 (#289)
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| LMArena Instruction Following | 1079 | 1031 |
Long Context DeepSeek LLM 67B leads
DeepSeek LLM 67B: 33.1 (#265), Qwen-14B: 31.3 (#280)
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| LMArena Longer Query | 1092 | 1028 |
Writing & Preference DeepSeek LLM 67B leads
DeepSeek LLM 67B: 31.6 (#282), Qwen-14B: 27.6 (#299)
| Benchmark | DeepSeek LLM 67B | Qwen-14B |
|---|---|---|
| LMArena Text | 1105 | 1051 |
| LMArena Creative Writing | 1067 | 1028 |
| LMArena Multi-Turn | 1082 | 1022 |
Frequently asked questions
Is DeepSeek LLM 67B better than Qwen-14B?
Qwen-14B is the stronger model overall, scoring 31.4 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or Qwen-14B better for coding?
They score almost the same on coding (31.9 vs 31.2); test both on your own repository before choosing.
How many benchmarks do DeepSeek LLM 67B and Qwen-14B share?
11 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Qwen-14B has 18.