Model comparison
DeepSeek-V2.5 (Sep 2024) vs Qwen Turbo
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 26.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in math, where DeepSeek-V2.5 (Sep 2024) leads 33.3 to 14.5.
- DeepSeek-V2.5 (Sep 2024) has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Qwen Turbo | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 37.0 | 26.8 |
| Released | 2024-09-06 | 2024-11-01 |
| Weights | Open | Proprietary |
| Context window | — | 1M |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.05 |
| Output $ / M tokens | — | $0.20 |
| Results tracked | 22 | 3 |
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Category by category
Coding Not comparable
DeepSeek-V2.5 (Sep 2024): 31.3 (#274), Qwen Turbo: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| LMArena Coding | 1310 | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Reasoning Not comparable
DeepSeek-V2.5 (Sep 2024): 24.5 (#145), Qwen Turbo: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| LMArena Hard Prompts | 1289 | — |
Math DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 33.3 (#177), Qwen Turbo: 14.5 (#291)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 6.1% |
| LMArena Math | 1289 | — |
| MATH Level 5 | — | 56.2% |
Knowledge DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 34.2 (#190), Qwen Turbo: 22.2 (#267)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| GPQA Diamond | — | 41.8% |
| LMArena Expert | 1266 | — |
Multilingual Not comparable
DeepSeek-V2.5 (Sep 2024): 42.7 (#188), Qwen Turbo: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| 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), Qwen Turbo: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| LMArena Instruction Following | 1280 | — |
Long Context Not comparable
DeepSeek-V2.5 (Sep 2024): 39.5 (#169), Qwen Turbo: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| LMArena Longer Query | 1301 | — |
Writing & Preference Not comparable
DeepSeek-V2.5 (Sep 2024): 50.0 (#182), Qwen Turbo: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen Turbo |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| LMArena Multi-Turn | 1297 | — |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Qwen Turbo?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 26.8 on the Noometry Index.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Qwen Turbo share?
0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Qwen Turbo has 3.