Model comparison
Gemma 2 27B vs GPT-5 Nano
GPT-5 Nano is the stronger model overall, scoring 33.5 to 29.4 on the Noometry Index.
Last verified . 22 shared benchmarks.
GoogleSummary
- They share 22 benchmarks with published results for both. Gemma 2 27B scores higher in 3 categories and GPT-5 Nano in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5 Nano leads 29.4 to 10.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.4% for Gemma 2 27B and 81.1% for GPT-5 Nano.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.65 / $0.65 for Gemma 2 27B.
- GPT-5 Nano accepts more context: 400K tokens versus 8K.
- Gemma 2 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 2 27B | GPT-5 Nano | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 29.4 | 33.5 |
| Released | 2024-06-24 | 2025-08-07 |
| Weights | Open | Proprietary |
| Context window | 8K | 400K |
| Max output | 2K | 128K |
| Input $ / M tokens | $0.65 | $0.05 |
| Output $ / M tokens | $0.65 | $0.40 |
| Results tracked | 34 | 49 |
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Category by category
Coding Too close to call
Gemma 2 27B: 34.1 (#246), GPT-5 Nano: 33.6 (#254)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| LMArena Coding | 1211 | 1351 |
| SWE-bench Verified (bash only) | — | 34.8% |
| WeirdML | — | 38.1% |
| BigCodeBench Instruct | 42.8% | — |
| LiveBench Coding | 36% | — |
| BigCodeBench Complete | 52.5% | — |
| ALE-Bench | — | 718.67 |
Agentic & Tool Use Not comparable
Gemma 2 27B: —, GPT-5 Nano: 25.8 (#106)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| Terminal-Bench | — | 21.8% |
| Berkeley Function Calling Leaderboard | — | 51.5% |
Reasoning Too close to call
Gemma 2 27B: 15.3 (#315), GPT-5 Nano: 16.3 (#306)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| LMArena Hard Prompts | 1198 | 1328 |
| DTBench | 48% | 62.7% |
| LMCA | 7.1% | 7.9% |
| Epoch Capabilities Index | 122.08 | 139.38 |
| ARC-AGI-2 | — | 2.6% |
| Kagi LLM Benchmark | — | 62.2% |
| ARC-AGI-1 | — | 20.7% |
| Chess Puzzles | — | 27% |
| LiveBench Reasoning | 28.1% | — |
| Mystery Game Puzzles | — | 9% |
| LiveBench Data Analysis | 47.9% | — |
| ForecastBench | — | 59.1 |
| LiveBench | 38.2% | — |
Math GPT-5 Nano leads
Gemma 2 27B: 10.7 (#311), GPT-5 Nano: 29.4 (#241)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.4% | 81.1% |
| LMArena Math | 1212 | 1317 |
| MATH Level 5 | 27.9% | 95.2% |
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| LiveBench Math | 26.5% | — |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge GPT-5 Nano leads
Gemma 2 27B: 19.0 (#280), GPT-5 Nano: 35.9 (#178)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| GPQA Diamond | 36.5% | 69.4% |
| LMArena Expert | 1172 | 1321 |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| Confabulations | 27.1% | — |
| Vectara Hallucination Rate | — | 10.5% |
| GPQA (HELM) | — | 67.9% |
| MMLU | 75.7% | — |
Multimodal Not comparable
Gemma 2 27B: —, GPT-5 Nano: 31.3 (#108)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |
Multilingual GPT-5 Nano leads
Gemma 2 27B: 38.6 (#226), GPT-5 Nano: 45.3 (#172)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | 1217 | 1313 |
| LMArena Chinese | 1221 | 1356 |
| LMArena German | 1209 | 1327 |
| LMArena Japanese | 1175 | 1226 |
| LMArena Korean | 1174 | 1269 |
| LMArena Russian | 1234 | 1296 |
| LMArena Spanish | 1228 | 1360 |
| LMArena French | 1247 | — |
Instruction Following GPT-5 Nano leads
Gemma 2 27B: 60.5 (#249), GPT-5 Nano: 75.0 (#79)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| LMArena Instruction Following | 1206 | 1306 |
| LiveBench Instruction Following | 58.1% | — |
| IFEval | — | 93.2% |
Long Context Gemma 2 27B leads
Gemma 2 27B: 37.3 (#218), GPT-5 Nano: 31.3 (#281)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| LMArena Longer Query | 1231 | 1312 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference Gemma 2 27B leads
Gemma 2 27B: 44.2 (#225), GPT-5 Nano: 39.1 (#249)
| Benchmark | Gemma 2 27B | GPT-5 Nano |
|---|---|---|
| LMArena Text | 1231 | 1320 |
| LMArena Creative Writing | 1241 | 1249 |
| LMArena Multi-Turn | 1224 | 1311 |
| EQ-Bench Creative Writing | — | 705 |
| WildBench | — | 80.6% |
| LiveBench Language | 32.6% | — |
Frequently asked questions
Is Gemma 2 27B better than GPT-5 Nano?
GPT-5 Nano is the stronger model overall, scoring 33.5 to 29.4 on the Noometry Index.
Which is cheaper, Gemma 2 27B or GPT-5 Nano?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Gemma 2 27B lists at $0.65 and $0.65.
Is Gemma 2 27B or GPT-5 Nano better for coding?
They score almost the same on coding (34.1 vs 33.6); test both on your own repository before choosing.
Which has the bigger context window?
GPT-5 Nano does, with 400K tokens against 8K.
How many benchmarks do Gemma 2 27B and GPT-5 Nano share?
22 benchmarks have published results for both models. Gemma 2 27B has 34 scored results on Noometry and GPT-5 Nano has 49.