Model comparison
Gemma 3 27B vs GPT-4.1 mini
GPT-4.1 mini is the stronger model overall, scoring 33.6 to 30.8 on the Noometry Index. Gemma 3 27B costs 7.0× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Last verified . 32 shared benchmarks.
GoogleSummary
- They share 32 benchmarks with published results for both. Gemma 3 27B scores higher in 4 categories and GPT-4.1 mini in 6 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-4.1 mini leads 34.7 to 25.5.
- The biggest single-benchmark swing is Aider Polyglot: 4.9% for Gemma 3 27B and 32.4% for GPT-4.1 mini.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 131K.
- Gemma 3 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 27B | GPT-4.1 mini | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 30.8 | 33.6 |
| Released | 2025-03-11 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 8K | 33K |
| Input $ / M tokens | $0.08 | $0.40 |
| Output $ / M tokens | $0.16 | $1.60 |
| Results tracked | 43 | 47 |
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Category by category
Coding GPT-4.1 mini leads
Gemma 3 27B: 22.5 (#334), GPT-4.1 mini: 30.6 (#293)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| Aider Polyglot | 4.9% | 32.4% |
| SciCode | 21.2% | 40.4% |
| LMArena Coding | 1322 | 1367 |
| SWE-bench Verified (bash only) | — | 23.9% |
| WeirdML | — | 37.6% |
| BigCodeBench Instruct | — | 48.9% |
| LiveBench Coding | 39.9% | — |
| CadEval | — | 16% |
Agentic & Tool Use GPT-4.1 mini leads
Gemma 3 27B: 25.1 (#110), GPT-4.1 mini: 33.3 (#55)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | 50.5% |
Reasoning Gemma 3 27B leads
Gemma 3 27B: 16.7 (#301), GPT-4.1 mini: 10.8 (#340)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| Kagi LLM Benchmark | 40.4% | 48.6% |
| CritPt | 0% | 0% |
| Chess Puzzles | 0% | 7% |
| LMArena Hard Prompts | 1340 | 1349 |
| DTBench | 52.5% | 68.8% |
| LMCA | 12.3% | 21.1% |
| Epoch Capabilities Index | 130.04 | 135.01 |
| ARC-AGI-2 | — | 0% |
| ARC-AGI-1 | — | 3.5% |
| LiveBench Reasoning | 43.8% | — |
| Mystery Game Puzzles | — | 7% |
| LiveBench Data Analysis | 51.5% | — |
| LiveBench | 50% | — |
Math Gemma 3 27B leads
Gemma 3 27B: 25.9 (#265), GPT-4.1 mini: 24.1 (#270)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 22.5% | 44.7% |
| LMArena Math | 1312 | 1343 |
| MATH Level 5 | 74% | 87.3% |
| FrontierMath (Tiers 1-3) | — | 6.7% |
| Omni-MATH | — | 49.1% |
| LiveBench Math | 55.4% | — |
| FrontierMath (Feb 2025 set) | — | 4.5% |
Knowledge GPT-4.1 mini leads
Gemma 3 27B: 25.5 (#261), GPT-4.1 mini: 34.7 (#194)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| GPQA Diamond | 47.7% | 65.8% |
| LMArena Expert | 1304 | 1338 |
| SimpleQA Verified | — | 12.7% |
| MMLU-Pro | — | 78.3% |
| Confabulations | 40.3% | — |
| Vectara Hallucination Rate | 7.4% | — |
| GPQA (HELM) | — | 61.4% |
Multimodal GPT-4.1 mini leads
Gemma 3 27B: 32.6 (#100), GPT-4.1 mini: 35.8 (#82)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | 1164 | 1181 |
| GeoBench | 52% | — |
Multilingual Gemma 3 27B leads
Gemma 3 27B: 46.9 (#155), GPT-4.1 mini: 45.7 (#166)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | 1334 | 1318 |
| LMArena Chinese | 1346 | 1329 |
| LMArena French | 1368 | 1358 |
| LMArena German | 1362 | 1351 |
| LMArena Japanese | 1287 | 1290 |
| LMArena Korean | 1308 | 1298 |
| LMArena Russian | 1349 | 1324 |
| LMArena Spanish | 1349 | 1319 |
Instruction Following GPT-4.1 mini leads
Gemma 3 27B: 70.6 (#160), GPT-4.1 mini: 73.7 (#118)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| LMArena Instruction Following | 1321 | 1333 |
| LiveBench Instruction Following | 74.9% | — |
| IFEval | — | 90.4% |
Long Context GPT-4.1 mini leads
Gemma 3 27B: 27.6 (#293), GPT-4.1 mini: 31.8 (#275)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| Fiction.LiveBench | 33.3% | 44.4% |
| LMArena Longer Query | 1333 | 1344 |
Writing & Preference Gemma 3 27B leads
Gemma 3 27B: 52.5 (#168), GPT-4.1 mini: 48.6 (#199)
| Benchmark | Gemma 3 27B | GPT-4.1 mini |
|---|---|---|
| LMArena Text | 1358 | 1340 |
| LMArena Creative Writing | 1346 | 1300 |
| EQ-Bench Creative Writing | 1266 | 1147 |
| LMArena Multi-Turn | 1345 | 1354 |
| Short-Story Creative Writing | 79.9% | — |
| WildBench | — | 83.8% |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than GPT-4.1 mini?
GPT-4.1 mini is the stronger model overall, scoring 33.6 to 30.8 on the Noometry Index. Gemma 3 27B costs 7.0× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 27B or GPT-4.1 mini?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.
Is Gemma 3 27B or GPT-4.1 mini better for coding?
GPT-4.1 mini scores higher on coding benchmarks: 30.6 versus 22.5 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 131K.
How many benchmarks do Gemma 3 27B and GPT-4.1 mini share?
32 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and GPT-4.1 mini has 47.