Model comparison
Gemma 7B vs GPT-5-Codex
GPT-5-Codex is the stronger model overall, scoring 37.9 to 30.0 on the Noometry Index.
Last verified . 0 shared benchmarks.
GoogleSummary
- The widest gap is in coding, where GPT-5-Codex leads 42.4 to 30.5.
- Gemma 7B has downloadable open weights; the other is API-only.
Side by side
| Gemma 7B | GPT-5-Codex | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 30.0 | 37.9 |
| Released | 2024-02-21 | 2025-09-15 |
| Weights | Open | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $1.25 |
| Output $ / M tokens | — | $10 |
| Results tracked | 27 | 3 |
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Category by category
Coding GPT-5-Codex leads
Gemma 7B: 30.5 (#294), GPT-5-Codex: 42.4 (#103)
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| WeirdML | — | 54.5% |
| LMArena Coding | 1048 | — |
| HumanEval+ | 28.7% | — |
| MBPP+ | 43.4% | — |
Agentic & Tool Use Not comparable
Gemma 7B: —, GPT-5-Codex: 31.0 (#72)
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| Terminal-Bench | — | 44.3% |
Reasoning GPT-5-Codex leads
Gemma 7B: 19.9 (#249), GPT-5-Codex: 30.9 (#83)
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| Kagi LLM Benchmark | — | 70.3% |
| LMArena Hard Prompts | 1042 | — |
| Adversarial NLI | 48.7% | — |
| BIG-Bench Hard | 55.1% | — |
| Epoch Capabilities Index | 111.99 | — |
| HellaSwag | 82.2% | — |
| PIQA | 81.2% | — |
| WinoGrande | 79% | — |
Math Not comparable
Gemma 7B: 31.2 (#228), GPT-5-Codex: —
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| LMArena Math | 1066 | — |
| GSM8K | 46.4% | — |
Knowledge Not comparable
Gemma 7B: 27.3 (#252), GPT-5-Codex: —
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| LMArena Expert | 1001 | — |
| ARC (AI2) Challenge | 78.3% | — |
| BoolQ | 83.2% | — |
| MMLU | 66.1% | — |
| OpenBookQA | 78.6% | — |
| TriviaQA | 72.3% | — |
Multilingual Not comparable
Gemma 7B: 25.1 (#287), GPT-5-Codex: —
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| LMArena Non-English | 999 | — |
| LMArena Chinese | 1035 | — |
| LMArena French | 1025 | — |
| LMArena Russian | 993 | — |
Instruction Following Not comparable
Gemma 7B: 51.5 (#295), GPT-5-Codex: —
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| LMArena Instruction Following | 1017 | — |
Long Context Not comparable
Gemma 7B: 31.1 (#282), GPT-5-Codex: —
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| LMArena Longer Query | 1022 | — |
Writing & Preference Not comparable
Gemma 7B: 27.1 (#302), GPT-5-Codex: —
| Benchmark | Gemma 7B | GPT-5-Codex |
|---|---|---|
| LMArena Text | 1056 | — |
| LMArena Creative Writing | 1024 | — |
| LMArena Multi-Turn | 963 | — |
Frequently asked questions
Is Gemma 7B better than GPT-5-Codex?
GPT-5-Codex is the stronger model overall, scoring 37.9 to 30.0 on the Noometry Index.
Is Gemma 7B or GPT-5-Codex better for coding?
GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 30.5 in the Noometry coding category.
How many benchmarks do Gemma 7B and GPT-5-Codex share?
0 benchmarks have published results for both models. Gemma 7B has 27 scored results on Noometry and GPT-5-Codex has 3.