Model comparison
DeepSeek-V3.1-Terminus vs Gemma 1.1 7b IT
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.3 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 1.1 7b IT 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 30.4.
Side by side
| DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 43.1 | 31.3 |
| Released | 2025-09-22 | — |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 147K | — |
| Input $ / M tokens | $0.27 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 19 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), Gemma 1.1 7b IT: 31.5 (#284)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Coding | 1426 | 1084 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
| HumanEval+ | — | 35.4% |
| MBPP+ | — | 45% |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 26.4 (#133), Gemma 1.1 7b IT: 20.5 (#238)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1071 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), Gemma 1.1 7b IT: 32.0 (#220)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Math | 1402 | 1107 |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Gemma 1.1 7b IT: 28.3 (#247)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Expert | — | 1039 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.1 (#92), Gemma 1.1 7b IT: 28.1 (#273)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Non-English | 1407 | 1052 |
| LMArena Russian | 1436 | 1046 |
| LMArena Chinese | — | 1061 |
| LMArena French | — | 1065 |
| LMArena German | — | 1054 |
| LMArena Japanese | — | 971 |
| LMArena Korean | — | 988 |
| LMArena Spanish | — | 1049 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.0 (#106), Gemma 1.1 7b IT: 54.0 (#283)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Instruction Following | 1404 | 1057 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.4 (#97), Gemma 1.1 7b IT: 32.1 (#272)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Longer Query | 1421 | 1056 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.0 (#92), Gemma 1.1 7b IT: 30.4 (#288)
| Benchmark | DeepSeek-V3.1-Terminus | Gemma 1.1 7b IT |
|---|---|---|
| LMArena Text | 1419 | 1094 |
| LMArena Creative Writing | 1403 | 1060 |
| LMArena Multi-Turn | 1411 | 1040 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Gemma 1.1 7b IT?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.3 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or Gemma 1.1 7b IT better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 31.5 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1-Terminus and Gemma 1.1 7b IT share?
10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Gemma 1.1 7b IT has 19.