Model comparison
DeepSeek-V3.1-Terminus vs Qwen2.5 Plus 1127
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 38.1 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 10 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Qwen2.5 Plus 1127 in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.3 to 49.5.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 42.6 | 38.1 |
| Released | 2025-09-22 | — |
| Weights | Open | Proprietary |
| Context window | 164K | — |
| Max output | 66K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 14 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 41.5 (#114), Qwen2.5 Plus 1127: 37.9 (#171)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Coding | 1426 | 1314 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
Reasoning Too close to call
DeepSeek-V3.1-Terminus: 25.7 (#126), Qwen2.5 Plus 1127: 24.8 (#139)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Hard Prompts | 1427 | 1299 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Qwen2.5 Plus 1127: 33.5 (#175)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Math | 1402 | 1298 |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Qwen2.5 Plus 1127: 34.9 (#179)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Expert | — | 1289 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.3 (#87), Qwen2.5 Plus 1127: 42.1 (#196)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Non-English | 1407 | 1265 |
| LMArena Russian | 1434 | 1271 |
| LMArena Chinese | — | 1314 |
| LMArena German | — | 1231 |
| LMArena Japanese | — | 1207 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.4 (#96), Qwen2.5 Plus 1127: 67.4 (#194)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Instruction Following | 1406 | 1275 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.5 (#88), Qwen2.5 Plus 1127: 39.2 (#180)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Longer Query | 1426 | 1292 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.3 (#87), Qwen2.5 Plus 1127: 49.5 (#186)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen2.5 Plus 1127 |
|---|---|---|
| LMArena Text | 1420 | 1299 |
| LMArena Creative Writing | 1404 | 1262 |
| LMArena Multi-Turn | 1411 | 1299 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Qwen2.5 Plus 1127?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 38.1 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or Qwen2.5 Plus 1127 better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 37.9 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1-Terminus and Qwen2.5 Plus 1127 share?
10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Qwen2.5 Plus 1127 has 14.