Model comparison
DeepSeek-V2.5 (Sep 2024) vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 37.0 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 34.2.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 37.0 | 41.9 |
| Released | 2024-09-06 | 2026-04-22 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $3.60 |
| Results tracked | 22 | 11 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Qwen3.6 27B leads
DeepSeek-V2.5 (Sep 2024): 31.3 (#274), Qwen3.6 27B: 38.5 (#162)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| Aider Polyglot | 17.8% | — |
| SciCode | — | 37.3% |
| BigCodeBench Instruct | 48.6% | — |
| LMArena Coding | 1310 | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Reasoning Too close to call
DeepSeek-V2.5 (Sep 2024): 24.5 (#145), Qwen3.6 27B: 24.4 (#148)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| CritPt | — | 0.9% |
| Chess Puzzles | — | 22% |
| LMArena Hard Prompts | 1289 | — |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 78.1% |
| LMCA | — | 34.5% |
| Epoch Capabilities Index | — | 146.47 |
Math Qwen3.6 27B leads
DeepSeek-V2.5 (Sep 2024): 33.3 (#177), Qwen3.6 27B: 47.5 (#56)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 35.1% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| LMArena Math | 1289 | — |
Knowledge Qwen3.6 27B leads
DeepSeek-V2.5 (Sep 2024): 34.2 (#190), Qwen3.6 27B: 52.4 (#58)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | — | 85.9% |
| LMArena Expert | 1266 | — |
Multilingual Not comparable
DeepSeek-V2.5 (Sep 2024): 42.7 (#188), Qwen3.6 27B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| 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), Qwen3.6 27B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| LMArena Instruction Following | 1280 | — |
Long Context Not comparable
DeepSeek-V2.5 (Sep 2024): 39.5 (#169), Qwen3.6 27B: —
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| LMArena Longer Query | 1301 | — |
Writing & Preference Too close to call
DeepSeek-V2.5 (Sep 2024): 50.0 (#182), Qwen3.6 27B: 50.3 (#180)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen3.6 27B |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| EQ-Bench 4 | — | 1026 |
| LMArena Multi-Turn | 1297 | — |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 37.0 on the Noometry Index.
Is DeepSeek-V2.5 (Sep 2024) or Qwen3.6 27B better for coding?
Qwen3.6 27B scores higher on coding benchmarks: 38.5 versus 31.3 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Qwen3.6 27B share?
0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Qwen3.6 27B has 11.