Model comparison
Gemma 3 27B vs GPT-5 Mini
GPT-5 Mini is the stronger model overall, scoring 41.8 to 30.8 on the Noometry Index. Gemma 3 27B costs 6.9× less per token, which makes it the better buy when GPT-5 Mini's lead doesn't matter for your workload.
Last verified . 34 shared benchmarks.
GoogleSummary
- They share 34 benchmarks with published results for both. Gemma 3 27B scores higher in 0 categories and GPT-5 Mini in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5 Mini leads 46.7 to 25.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 22.5% for Gemma 3 27B and 86.7% for GPT-5 Mini.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $0.25 / $2 for GPT-5 Mini.
- GPT-5 Mini accepts more context: 400K tokens versus 131K.
- Gemma 3 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 27B | GPT-5 Mini | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 30.8 | 41.8 |
| Released | 2025-03-11 | 2025-08-07 |
| Weights | Open | Proprietary |
| Context window | 131K | 400K |
| Max output | 8K | 128K |
| Input $ / M tokens | $0.08 | $0.25 |
| Output $ / M tokens | $0.16 | $2 |
| Results tracked | 43 | 60 |
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Category by category
Coding GPT-5 Mini leads
Gemma 3 27B: 22.5 (#334), GPT-5 Mini: 40.1 (#146)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| SciCode | 21.2% | 39.2% |
| LMArena Coding | 1322 | 1406 |
| SWE-bench Verified | — | 64.7% |
| SWE-bench Verified (bash only) | — | 59.8% |
| Aider Polyglot | 4.9% | — |
| SWE-bench Multilingual | — | 39.7% |
| WeirdML | — | 52.7% |
| LiveBench Coding | 39.9% | — |
| ALE-Bench | — | 799.77 |
| AlgoTune | — | 1.38 |
Agentic & Tool Use GPT-5 Mini leads
Gemma 3 27B: 25.1 (#110), GPT-5 Mini: 31.1 (#70)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | 55.5% |
| Terminal-Bench | — | 34.8% |
| Vending-Bench 2 | — | -31.18 |
Reasoning GPT-5 Mini leads
Gemma 3 27B: 16.7 (#301), GPT-5 Mini: 23.9 (#168)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| Kagi LLM Benchmark | 40.4% | 70.3% |
| CritPt | 0% | 0% |
| Chess Puzzles | 0% | 30% |
| LMArena Hard Prompts | 1340 | 1380 |
| DTBench | 52.5% | 80.5% |
| LMCA | 12.3% | 34.2% |
| Epoch Capabilities Index | 130.04 | 145.52 |
| ARC-AGI-2 | — | 4.4% |
| ARC-AGI-1 | — | 54.3% |
| EnigmaEval | — | 8.2% |
| LiveBench Reasoning | 43.8% | — |
| Mystery Game Puzzles | — | 10% |
| LiveBench Data Analysis | 51.5% | — |
| ForecastBench | — | 61 |
| LiveBench | 50% | — |
Math GPT-5 Mini leads
Gemma 3 27B: 25.9 (#265), GPT-5 Mini: 46.7 (#69)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 22.5% | 86.7% |
| LMArena Math | 1312 | 1378 |
| MATH Level 5 | 74% | 97.8% |
| FrontierMath (Tiers 1-3) | — | 46.7% |
| FrontierMath Tier 4 | — | 12.2% |
| ProofBench | — | 9% |
| Omni-MATH | — | 72.2% |
| LiveBench Math | 55.4% | — |
| FrontierMath (Feb 2025 set) | — | 27.2% |
| FrontierMath Tier 4 (v1) | — | 6.3% |
Knowledge GPT-5 Mini leads
Gemma 3 27B: 25.5 (#261), GPT-5 Mini: 45.6 (#86)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| GPQA Diamond | 47.7% | 75% |
| Confabulations | 40.3% | 13.3% |
| Vectara Hallucination Rate | 7.4% | 12.9% |
| LMArena Expert | 1304 | 1379 |
| Humanity's Last Exam | — | 19.4% |
| SimpleQA Verified | — | 21.6% |
| MMLU-Pro | — | 83.5% |
| GPQA (HELM) | — | 75.6% |
Multimodal GPT-5 Mini leads
Gemma 3 27B: 32.6 (#100), GPT-5 Mini: 35.6 (#85)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| LMArena Vision | 1164 | 1202 |
| GeoBench | 52% | — |
| VPCT | — | 40.2% |
Multilingual GPT-5 Mini leads
Gemma 3 27B: 46.9 (#155), GPT-5 Mini: 48.9 (#137)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| LMArena Non-English | 1334 | 1363 |
| LMArena Chinese | 1346 | 1385 |
| LMArena French | 1368 | 1386 |
| LMArena German | 1362 | 1366 |
| LMArena Japanese | 1287 | 1341 |
| LMArena Korean | 1308 | 1308 |
| LMArena Russian | 1349 | 1362 |
| LMArena Spanish | 1349 | 1355 |
Instruction Following GPT-5 Mini leads
Gemma 3 27B: 70.6 (#160), GPT-5 Mini: 76.2 (#46)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| LMArena Instruction Following | 1321 | 1357 |
| LiveBench Instruction Following | 74.9% | — |
| IFEval | — | 92.7% |
Long Context GPT-5 Mini leads
Gemma 3 27B: 27.6 (#293), GPT-5 Mini: 41.9 (#132)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| Fiction.LiveBench | 33.3% | 69.4% |
| LMArena Longer Query | 1333 | 1355 |
Writing & Preference GPT-5 Mini leads
Gemma 3 27B: 52.5 (#168), GPT-5 Mini: 55.2 (#148)
| Benchmark | Gemma 3 27B | GPT-5 Mini |
|---|---|---|
| LMArena Text | 1358 | 1373 |
| LMArena Creative Writing | 1346 | 1325 |
| Short-Story Creative Writing | 79.9% | 83.1% |
| EQ-Bench Creative Writing | 1266 | 1313 |
| LMArena Multi-Turn | 1345 | 1363 |
| WildBench | — | 85.5% |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than GPT-5 Mini?
GPT-5 Mini is the stronger model overall, scoring 41.8 to 30.8 on the Noometry Index. Gemma 3 27B costs 6.9× less per token, which makes it the better buy when GPT-5 Mini's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 27B or GPT-5 Mini?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; GPT-5 Mini lists at $0.25 and $2.
Is Gemma 3 27B or GPT-5 Mini better for coding?
GPT-5 Mini scores higher on coding benchmarks: 40.1 versus 22.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5 Mini does, with 400K tokens against 131K.
How many benchmarks do Gemma 3 27B and GPT-5 Mini share?
34 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and GPT-5 Mini has 60.