Model comparison
DeepSeek-V2.5 (Sep 2024) vs Qwen2.5-VL 72B Instruct
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 29.4 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where DeepSeek-V2.5 (Sep 2024) leads 24.5 to 20.0.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 37.0 | 29.4 |
| Released | 2024-09-06 | 2024-09 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $2.80 |
| Output $ / M tokens | — | $8.40 |
| Results tracked | 22 | 6 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Not comparable
DeepSeek-V2.5 (Sep 2024): 31.3 (#274), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| LMArena Coding | 1310 | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Agentic & Tool Use Not comparable
DeepSeek-V2.5 (Sep 2024): —, Qwen2.5-VL 72B Instruct: 18.4 (#136)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OSWorld | — | 5% |
Reasoning DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 24.5 (#145), Qwen2.5-VL 72B Instruct: 20.0 (#228)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 36% |
| LMArena Hard Prompts | 1289 | — |
Math Not comparable
DeepSeek-V2.5 (Sep 2024): 33.3 (#177), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Math | 1289 | — |
Knowledge Not comparable
DeepSeek-V2.5 (Sep 2024): 34.2 (#190), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Expert | 1266 | — |
Multimodal Not comparable
DeepSeek-V2.5 (Sep 2024): —, Qwen2.5-VL 72B Instruct: 32.9 (#92)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | — | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
DeepSeek-V2.5 (Sep 2024): 42.7 (#188), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1273 | — |
| LMArena Chinese | 1317 | — |
| LMArena French | 1288 | — |
| LMArena German | 1258 | — |
| LMArena Japanese | 1228 | — |
| LMArena Korean | 1209 | — |
| LMArena Russian | 1289 | — |
| LMArena Spanish | 1248 | — |
Instruction Following Not comparable
DeepSeek-V2.5 (Sep 2024): 67.7 (#189), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1280 | — |
Long Context Not comparable
DeepSeek-V2.5 (Sep 2024): 39.5 (#169), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1301 | — |
Writing & Preference Not comparable
DeepSeek-V2.5 (Sep 2024): 50.0 (#182), Qwen2.5-VL 72B Instruct: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| LMArena Multi-Turn | 1297 | — |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Qwen2.5-VL 72B Instruct?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 29.4 on the Noometry Index.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Qwen2.5-VL 72B Instruct share?
0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.