Model comparison
DeepSeek LLM 67B vs Qwen2.5-VL 72B Instruct
Qwen2.5-VL 72B Instruct is the stronger model overall, scoring 29.9 to 24.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in reasoning, where Qwen2.5-VL 72B Instruct leads 20.7 to 16.5.
Side by side
| DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 24.9 | 29.9 |
| Released | 2023-11-29 | 2024-09 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $2.80 |
| Output $ / M tokens | — | $8.40 |
| Results tracked | 15 | 6 |
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Category by category
Coding Not comparable
DeepSeek LLM 67B: 31.9 (#278), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Coding | 1096 | — |
Agentic & Tool Use Not comparable
DeepSeek LLM 67B: —, Qwen2.5-VL 72B Instruct: 18.6 (#144)
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OSWorld | — | 5% |
Reasoning Qwen2.5-VL 72B Instruct leads
DeepSeek LLM 67B: 16.5 (#304), Qwen2.5-VL 72B Instruct: 20.7 (#233)
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 36% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1070 | — |
| Epoch Capabilities Index | 110.5 | — |
Math Not comparable
DeepSeek LLM 67B: 8.7 (#324), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| LMArena Math | 1108 | — |
| MATH Level 5 | 6.4% | — |
Knowledge Not comparable
DeepSeek LLM 67B: 7.0 (#313), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 24.6% | — |
Multimodal Not comparable
DeepSeek LLM 67B: —, Qwen2.5-VL 72B Instruct: 33.5 (#97)
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | — | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
DeepSeek LLM 67B: 29.4 (#267), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1073 | — |
| LMArena Chinese | 1132 | — |
Instruction Following Not comparable
DeepSeek LLM 67B: 55.4 (#277), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1079 | — |
Long Context Not comparable
DeepSeek LLM 67B: 33.1 (#265), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1092 | — |
Writing & Preference Not comparable
DeepSeek LLM 67B: 31.6 (#282), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek LLM 67B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1105 | — |
| LMArena Creative Writing | 1067 | — |
| LMArena Multi-Turn | 1082 | — |
Frequently asked questions
Is DeepSeek LLM 67B better than Qwen2.5-VL 72B Instruct?
Qwen2.5-VL 72B Instruct is the stronger model overall, scoring 29.9 to 24.9 on the Noometry Index.
How many benchmarks do DeepSeek LLM 67B and Qwen2.5-VL 72B Instruct share?
0 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.