Model comparison
DeepSeek LLM 67B vs Qwen3-1.7B
Qwen3-1.7B is the stronger model overall, scoring 26.6 to 24.9 on the Noometry Index.
Last verified . 3 shared benchmarks.
Summary
- They share 3 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and Qwen3-1.7B in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-1.7B leads 19.6 to 7.0.
- The biggest single-benchmark swing is GPQA Diamond: 24.6% for DeepSeek LLM 67B and 38% for Qwen3-1.7B.
Side by side
| DeepSeek LLM 67B | Qwen3-1.7B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 24.9 | 26.6 |
| Released | 2023-11-29 | 2025-04-29 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 15 | 4 |
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Category by category
Coding Not comparable
DeepSeek LLM 67B: 31.9 (#278), Qwen3-1.7B: —
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| LMArena Coding | 1096 | — |
Agentic & Tool Use Not comparable
DeepSeek LLM 67B: —, Qwen3-1.7B: 24.7 (#115)
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
Reasoning Qwen3-1.7B leads
DeepSeek LLM 67B: 16.5 (#304), Qwen3-1.7B: 19.2 (#267)
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| LMArena Hard Prompts | 1070 | — |
| Epoch Capabilities Index | 110.5 | — |
Math Qwen3-1.7B leads
DeepSeek LLM 67B: 8.7 (#324), Qwen3-1.7B: 16.3 (#294)
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 8.1% |
| LMArena Math | 1108 | — |
| MATH Level 5 | 6.4% | — |
Knowledge Qwen3-1.7B leads
DeepSeek LLM 67B: 7.0 (#313), Qwen3-1.7B: 19.6 (#278)
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 24.6% | 38% |
Multilingual Not comparable
DeepSeek LLM 67B: 29.4 (#267), Qwen3-1.7B: —
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1073 | — |
| LMArena Chinese | 1132 | — |
Instruction Following Not comparable
DeepSeek LLM 67B: 55.4 (#277), Qwen3-1.7B: —
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1079 | — |
Long Context Not comparable
DeepSeek LLM 67B: 33.1 (#265), Qwen3-1.7B: —
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1092 | — |
Writing & Preference Not comparable
DeepSeek LLM 67B: 31.6 (#282), Qwen3-1.7B: —
| Benchmark | DeepSeek LLM 67B | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1105 | — |
| LMArena Creative Writing | 1067 | — |
| LMArena Multi-Turn | 1082 | — |
Frequently asked questions
Is DeepSeek LLM 67B better than Qwen3-1.7B?
Qwen3-1.7B is the stronger model overall, scoring 26.6 to 24.9 on the Noometry Index.
How many benchmarks do DeepSeek LLM 67B and Qwen3-1.7B share?
3 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Qwen3-1.7B has 4.