Model comparison
DeepSeek-V3.1 vs Hunyuan Standard 2025 02 10
DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 37.2 on the Noometry Index.
Last verified . 12 shared benchmarks.
DeepSeek
TencentSummary
- They share 12 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 7 categories and Hunyuan Standard 2025 02 10 in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1 leads 60.5 to 47.4.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 | |
|---|---|---|
| Provider | DeepSeek | Tencent |
| Noometry Index | 42.2 | 37.2 |
| Released | 2025-08-21 | — |
| Weights | Open | Proprietary |
| Context window | 164K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.25 | — |
| Output $ / M tokens | $0.95 | — |
| Results tracked | 27 | 12 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek-V3.1 leads
DeepSeek-V3.1: 39.8 (#140), Hunyuan Standard 2025 02 10: 36.5 (#192)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Coding | 1417 | 1270 |
| WeirdML | 38.4% | — |
Reasoning DeepSeek-V3.1 leads
DeepSeek-V3.1: 27.3 (#109), Hunyuan Standard 2025 02 10: 23.9 (#157)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1264 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| Epoch Capabilities Index | 139.92 | — |
| ForecastBench | 58 | — |
Math DeepSeek-V3.1 leads
DeepSeek-V3.1: 36.1 (#125), Hunyuan Standard 2025 02 10: 33.0 (#179)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Math | 1420 | 1274 |
Knowledge DeepSeek-V3.1 leads
DeepSeek-V3.1: 43.0 (#86), Hunyuan Standard 2025 02 10: 33.6 (#192)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Expert | 1403 | 1248 |
| Vectara Hallucination Rate | 5.5% | — |
Multilingual DeepSeek-V3.1 leads
DeepSeek-V3.1: 51.8 (#100), Hunyuan Standard 2025 02 10: 41.9 (#198)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Non-English | 1400 | 1262 |
| LMArena Chinese | 1470 | 1319 |
| LMArena Russian | 1405 | 1258 |
| LMArena French | 1447 | — |
| LMArena German | 1412 | — |
| LMArena Japanese | 1374 | — |
| LMArena Korean | 1337 | — |
| LMArena Spanish | 1429 | — |
Instruction Following DeepSeek-V3.1 leads
DeepSeek-V3.1: 74.1 (#105), Hunyuan Standard 2025 02 10: 65.8 (#214)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Instruction Following | 1400 | 1245 |
Long Context Hunyuan Standard 2025 02 10 leads
DeepSeek-V3.1: 36.3 (#227), Hunyuan Standard 2025 02 10: 39.5 (#168)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Longer Query | 1422 | 1301 |
| Fiction.LiveBench | 52.8% | — |
Writing & Preference DeepSeek-V3.1 leads
DeepSeek-V3.1: 60.5 (#93), Hunyuan Standard 2025 02 10: 47.4 (#209)
| Benchmark | DeepSeek-V3.1 | Hunyuan Standard 2025 02 10 |
|---|---|---|
| LMArena Text | 1420 | 1274 |
| LMArena Creative Writing | 1401 | 1242 |
| LMArena Multi-Turn | 1408 | 1275 |
| EQ-Bench Creative Writing | 1436 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than Hunyuan Standard 2025 02 10?
DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 37.2 on the Noometry Index.
Is DeepSeek-V3.1 or Hunyuan Standard 2025 02 10 better for coding?
DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 36.5 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1 and Hunyuan Standard 2025 02 10 share?
12 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Hunyuan Standard 2025 02 10 has 12.