Model comparison
DeepSeek-V3.1 vs Granite 4.2 30b
DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 41.8 on the Noometry Index.
Last verified . 11 shared benchmarks.
DeepSeekSummary
- They share 11 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 5 categories and Granite 4.2 30b in 2 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1 leads 60.3 to 53.8.
Side by side
| DeepSeek-V3.1 | Granite 4.2 30b | |
|---|---|---|
| Provider | DeepSeek | IBM |
| Noometry Index | 42.8 | 41.8 |
| Released | 2025-08-21 | — |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.25 | — |
| Output $ / M tokens | $0.95 | — |
| Results tracked | 27 | 11 |
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Category by category
Coding Too close to call
DeepSeek-V3.1: 40.3 (#144), Granite 4.2 30b: 41.0 (#126)
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Coding | 1417 | 1396 |
| WeirdML | 38.4% | — |
Reasoning Too close to call
DeepSeek-V3.1: 27.9 (#110), Granite 4.2 30b: 27.8 (#112)
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1374 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| Epoch Capabilities Index | 139.92 | — |
| ForecastBench | 58 | — |
Math Not comparable
DeepSeek-V3.1: 38.9 (#122), Granite 4.2 30b: —
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Math | 1420 | — |
Knowledge DeepSeek-V3.1 leads
DeepSeek-V3.1: 43.7 (#90), Granite 4.2 30b: 39.1 (#138)
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Expert | 1405 | 1406 |
| Vectara Hallucination Rate | 5.5% | — |
Multilingual DeepSeek-V3.1 leads
DeepSeek-V3.1: 51.6 (#106), Granite 4.2 30b: 47.3 (#151)
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Non-English | 1400 | 1340 |
| LMArena Chinese | 1469 | 1414 |
| LMArena Russian | 1405 | 1343 |
| LMArena French | 1447 | — |
| LMArena German | 1411 | — |
| LMArena Japanese | 1378 | — |
| LMArena Korean | 1337 | — |
| LMArena Spanish | 1431 | — |
Instruction Following DeepSeek-V3.1 leads
DeepSeek-V3.1: 73.9 (#110), Granite 4.2 30b: 71.2 (#155)
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Instruction Following | 1400 | 1347 |
Long Context Granite 4.2 30b leads
DeepSeek-V3.1: 36.3 (#232), Granite 4.2 30b: 41.4 (#140)
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Longer Query | 1422 | 1359 |
| Fiction.LiveBench | 52.8% | — |
Writing & Preference DeepSeek-V3.1 leads
DeepSeek-V3.1: 60.3 (#98), Granite 4.2 30b: 53.8 (#156)
| Benchmark | DeepSeek-V3.1 | Granite 4.2 30b |
|---|---|---|
| LMArena Text | 1420 | 1361 |
| LMArena Creative Writing | 1401 | 1288 |
| LMArena Multi-Turn | 1408 | 1339 |
| EQ-Bench Creative Writing | 1436 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than Granite 4.2 30b?
DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 41.8 on the Noometry Index.
Is DeepSeek-V3.1 or Granite 4.2 30b better for coding?
They score almost the same on coding (40.3 vs 41.0); test both on your own repository before choosing.
How many benchmarks do DeepSeek-V3.1 and Granite 4.2 30b share?
11 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Granite 4.2 30b has 11.