Model comparison
Gemma 3n E4b IT vs GPT-5 Nano
Gemma 3n E4b IT is the stronger model overall, scoring 37.3 to 33.5 on the Noometry Index.
Last verified . 17 shared benchmarks.
GoogleSummary
- They share 17 benchmarks with published results for both. Gemma 3n E4b IT scores higher in 5 categories and GPT-5 Nano in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Gemma 3n E4b IT leads 50.1 to 39.1.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 31.5% for Gemma 3n E4b IT and 62.2% for GPT-5 Nano.
- Gemma 3n E4b IT has downloadable open weights; the other is API-only.
Side by side
| Gemma 3n E4b IT | GPT-5 Nano | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 37.3 | 33.5 |
| Released | — | 2025-08-07 |
| Weights | Open | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $0.05 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 18 | 49 |
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Category by category
Coding Gemma 3n E4b IT leads
Gemma 3n E4b IT: 37.0 (#198), GPT-5 Nano: 33.6 (#254)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Coding | 1268 | 1351 |
| SWE-bench Verified (bash only) | — | 34.8% |
| WeirdML | — | 38.1% |
| ALE-Bench | — | 718.67 |
Agentic & Tool Use Not comparable
Gemma 3n E4b IT: —, GPT-5 Nano: 25.8 (#106)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| Terminal-Bench | — | 21.8% |
| Berkeley Function Calling Leaderboard | — | 51.5% |
Reasoning Gemma 3n E4b IT leads
Gemma 3n E4b IT: 19.9 (#247), GPT-5 Nano: 16.3 (#306)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| Kagi LLM Benchmark | 31.5% | 62.2% |
| LMArena Hard Prompts | 1284 | 1328 |
| ARC-AGI-2 | — | 2.6% |
| ARC-AGI-1 | — | 20.7% |
| Chess Puzzles | — | 27% |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 62.7% |
| LMCA | — | 7.9% |
| Epoch Capabilities Index | — | 139.38 |
| ForecastBench | — | 59.1 |
Math Gemma 3n E4b IT leads
Gemma 3n E4b IT: 35.1 (#188), GPT-5 Nano: 29.4 (#241)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Math | 1251 | 1317 |
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| OTIS Mock AIME 2024-2025 | — | 81.1% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge GPT-5 Nano leads
Gemma 3n E4b IT: 34.2 (#198), GPT-5 Nano: 35.9 (#178)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Expert | 1246 | 1321 |
| GPQA Diamond | — | 69.4% |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| Vectara Hallucination Rate | — | 10.5% |
| GPQA (HELM) | — | 67.9% |
Multimodal Not comparable
Gemma 3n E4b IT: —, GPT-5 Nano: 31.3 (#108)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |
Multilingual GPT-5 Nano leads
Gemma 3n E4b IT: 43.4 (#183), GPT-5 Nano: 45.3 (#172)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | 1285 | 1313 |
| LMArena Chinese | 1309 | 1356 |
| LMArena German | 1311 | 1327 |
| LMArena Japanese | 1272 | 1226 |
| LMArena Korean | 1259 | 1269 |
| LMArena Russian | 1288 | 1296 |
| LMArena Spanish | 1305 | 1360 |
| LMArena French | 1330 | — |
Instruction Following GPT-5 Nano leads
Gemma 3n E4b IT: 66.1 (#210), GPT-5 Nano: 75.0 (#79)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Instruction Following | 1255 | 1306 |
| IFEval | — | 93.2% |
Long Context Gemma 3n E4b IT leads
Gemma 3n E4b IT: 38.7 (#191), GPT-5 Nano: 31.3 (#281)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Longer Query | 1276 | 1312 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference Gemma 3n E4b IT leads
Gemma 3n E4b IT: 50.1 (#186), GPT-5 Nano: 39.1 (#249)
| Benchmark | Gemma 3n E4b IT | GPT-5 Nano |
|---|---|---|
| LMArena Text | 1306 | 1320 |
| LMArena Creative Writing | 1287 | 1249 |
| LMArena Multi-Turn | 1276 | 1311 |
| EQ-Bench Creative Writing | — | 705 |
| WildBench | — | 80.6% |
Frequently asked questions
Is Gemma 3n E4b IT better than GPT-5 Nano?
Gemma 3n E4b IT is the stronger model overall, scoring 37.3 to 33.5 on the Noometry Index.
Is Gemma 3n E4b IT or GPT-5 Nano better for coding?
Gemma 3n E4b IT scores higher on coding benchmarks: 37.0 versus 33.6 in the Noometry coding category.
How many benchmarks do Gemma 3n E4b IT and GPT-5 Nano share?
17 benchmarks have published results for both models. Gemma 3n E4b IT has 18 scored results on Noometry and GPT-5 Nano has 49.