Model comparison
DeepSeek-V3.1-Terminus vs Gemma 7B
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 30.0 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeek
GoogleSummary
- They share 10 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Gemma 7B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 27.1.
Side by side
| DeepSeek-V3.1-Terminus | Gemma 7B | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 43.1 | 30.0 |
| Released | 2025-09-22 | 2024-02-21 |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 147K | — |
| Input $ / M tokens | $0.27 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 27 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), Gemma 7B: 30.5 (#294)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Coding | 1426 | 1048 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
| HumanEval+ | — | 28.7% |
| MBPP+ | — | 43.4% |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 26.4 (#133), Gemma 7B: 19.9 (#249)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1042 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Adversarial NLI | — | 48.7% |
| BIG-Bench Hard | — | 55.1% |
| Epoch Capabilities Index | — | 111.99 |
| HellaSwag | — | 82.2% |
| PIQA | — | 81.2% |
| WinoGrande | — | 79% |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), Gemma 7B: 31.2 (#228)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Math | 1402 | 1066 |
| GSM8K | — | 46.4% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Gemma 7B: 27.3 (#252)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Expert | — | 1001 |
| ARC (AI2) Challenge | — | 78.3% |
| BoolQ | — | 83.2% |
| MMLU | — | 66.1% |
| OpenBookQA | — | 78.6% |
| TriviaQA | — | 72.3% |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.1 (#92), Gemma 7B: 25.1 (#287)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Non-English | 1407 | 999 |
| LMArena Russian | 1436 | 993 |
| LMArena Chinese | — | 1035 |
| LMArena French | — | 1025 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.0 (#106), Gemma 7B: 51.5 (#295)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1017 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.4 (#97), Gemma 7B: 31.1 (#282)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Longer Query | 1421 | 1022 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.0 (#92), Gemma 7B: 27.1 (#302)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 7B |
|---|---|---|
| LMArena Text | 1419 | 1056 |
| LMArena Creative Writing | 1403 | 1024 |
| LMArena Multi-Turn | 1411 | 963 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Gemma 7B?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 30.0 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or Gemma 7B better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 30.5 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1-Terminus and Gemma 7B share?
10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Gemma 7B has 27.