Model comparison
DeepSeek-V3.1 vs Gemma 2B
DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 29.1 on the Noometry Index.
Last verified . 12 shared benchmarks.
DeepSeek
GoogleSummary
- They share 12 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 7 categories and Gemma 2B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1 leads 60.5 to 24.1.
Side by side
| DeepSeek-V3.1 | Gemma 2B | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 42.2 | 29.1 |
| Released | 2025-08-21 | 2024-02-21 |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.25 | — |
| Output $ / M tokens | $0.95 | — |
| Results tracked | 27 | 23 |
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Category by category
Coding DeepSeek-V3.1 leads
DeepSeek-V3.1: 39.8 (#140), Gemma 2B: 28.9 (#300)
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| LMArena Coding | 1417 | 1010 |
| WeirdML | 38.4% | — |
| HumanEval+ | — | 20.7% |
| MBPP+ | — | 34.1% |
Reasoning DeepSeek-V3.1 leads
DeepSeek-V3.1: 27.3 (#109), Gemma 2B: 17.9 (#275)
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| LMArena Hard Prompts | 1417 | 989 |
| Epoch Capabilities Index | 139.92 | 93.57 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| BIG-Bench Hard | — | 35.2% |
| ForecastBench | 58 | — |
| HellaSwag | — | 71.4% |
| PIQA | — | 77.3% |
| WinoGrande | — | 65.4% |
Math DeepSeek-V3.1 leads
DeepSeek-V3.1: 36.1 (#125), Gemma 2B: 27.6 (#237)
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| LMArena Math | 1420 | 1009 |
| GSM8K | — | 17.7% |
Knowledge Not comparable
DeepSeek-V3.1: 43.0 (#86), Gemma 2B: —
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| Vectara Hallucination Rate | 5.5% | — |
| LMArena Expert | 1403 | — |
| ARC (AI2) Challenge | — | 42.1% |
| BoolQ | — | 69.4% |
| MMLU | — | 42.3% |
| TriviaQA | — | 53.2% |
Multilingual DeepSeek-V3.1 leads
DeepSeek-V3.1: 51.8 (#100), Gemma 2B: 23.1 (#289)
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| LMArena Non-English | 1400 | 958 |
| LMArena Chinese | 1470 | 986 |
| LMArena Russian | 1405 | 937 |
| 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), Gemma 2B: 48.8 (#297)
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| LMArena Instruction Following | 1400 | 971 |
Long Context DeepSeek-V3.1 leads
DeepSeek-V3.1: 36.3 (#227), Gemma 2B: 29.9 (#286)
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| LMArena Longer Query | 1422 | 981 |
| Fiction.LiveBench | 52.8% | — |
Writing & Preference DeepSeek-V3.1 leads
DeepSeek-V3.1: 60.5 (#93), Gemma 2B: 24.1 (#303)
| Benchmark | DeepSeek-V3.1 | Gemma 2B |
|---|---|---|
| LMArena Text | 1420 | 1002 |
| LMArena Creative Writing | 1401 | 986 |
| LMArena Multi-Turn | 1408 | 945 |
| EQ-Bench Creative Writing | 1436 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than Gemma 2B?
DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 29.1 on the Noometry Index.
Is DeepSeek-V3.1 or Gemma 2B better for coding?
DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 28.9 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1 and Gemma 2B share?
12 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Gemma 2B has 23.