Model comparison
Gemma 3 12B vs GPT-4 Turbo
Gemma 3 12B is the stronger model overall, scoring 31.8 to 30.3 on the Noometry Index.
Last verified . 18 shared benchmarks.
GoogleSummary
- They share 18 benchmarks with published results for both. Gemma 3 12B scores higher in 6 categories and GPT-4 Turbo in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemma 3 12B leads 21.0 to 8.6.
- The biggest single-benchmark swing is DTBench: 48.8% for Gemma 3 12B and 61.6% for GPT-4 Turbo.
- Gemma 3 12B is cheaper at $0.05 / $0.15 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
- Gemma 3 12B accepts more context: 131K tokens versus 128K.
- Gemma 3 12B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 12B | GPT-4 Turbo | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 31.8 | 30.3 |
| Released | 2025-03-12 | 2023-11-06 |
| Weights | Open | Proprietary |
| Context window | 131K | 128K |
| Max output | 8K | 4K |
| Input $ / M tokens | $0.05 | $10 |
| Output $ / M tokens | $0.15 | $30 |
| Results tracked | 24 | 36 |
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Category by category
Coding GPT-4 Turbo leads
Gemma 3 12B: 31.2 (#276), GPT-4 Turbo: 33.4 (#247)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| LMArena Coding | 1281 | 1268 |
| SciCode | 17.4% | — |
| WeirdML | — | 18% |
| BigCodeBench Instruct | — | 48.2% |
| BigCodeBench Complete | — | 58.2% |
| HumanEval+ | — | 86.6% |
| MBPP+ | — | 73.3% |
Agentic & Tool Use Not comparable
Gemma 3 12B: 25.3 (#101), GPT-4 Turbo: —
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| Berkeley Function Calling Leaderboard | 30.4% | — |
| METR Time Horizons | — | 36.7% |
Reasoning Too close to call
Gemma 3 12B: 15.2 (#307), GPT-4 Turbo: 14.9 (#311)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| Chess Puzzles | 0% | 6% |
| LMArena Hard Prompts | 1309 | 1251 |
| DTBench | 48.8% | 61.6% |
| LMCA | 4.5% | 9.8% |
| Epoch Capabilities Index | 123.49 | 127.25 |
| SimpleBench | — | 25.1% |
| CritPt | 0% | — |
| ForecastBench | — | 59.4 |
Math Gemma 3 12B leads
Gemma 3 12B: 21.0 (#273), GPT-4 Turbo: 8.6 (#316)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.7% | 6.7% |
| LMArena Math | 1307 | 1272 |
| FrontierMath (Tiers 1-3) | — | 0.7% |
| MATH Level 5 | — | 46.7% |
Knowledge Gemma 3 12B leads
Gemma 3 12B: 26.5 (#250), GPT-4 Turbo: 24.3 (#263)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| GPQA Diamond | 39.5% | 46.6% |
| LMArena Expert | 1248 | 1223 |
| Confabulations | — | 28.4% |
| Vectara Hallucination Rate | 4.4% | — |
| MMLU | — | 81.3% |
Multimodal Not comparable
Gemma 3 12B: —, GPT-4 Turbo: 30.0 (#104)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| LMArena Vision | — | 1090 |
| MindCube | 46.7% | — |
Multilingual Gemma 3 12B leads
Gemma 3 12B: 45.9 (#160), GPT-4 Turbo: 40.7 (#211)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| LMArena Non-English | 1318 | 1245 |
| LMArena German | 1370 | 1259 |
| LMArena Russian | 1335 | 1259 |
| LMArena Chinese | — | 1242 |
| LMArena French | — | 1275 |
| LMArena Japanese | — | 1194 |
| LMArena Korean | — | 1187 |
| LMArena Spanish | — | 1260 |
Instruction Following Gemma 3 12B leads
Gemma 3 12B: 68.8 (#179), GPT-4 Turbo: 66.0 (#211)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| LMArena Instruction Following | 1299 | 1250 |
Long Context Gemma 3 12B leads
Gemma 3 12B: 40.0 (#157), GPT-4 Turbo: 38.0 (#200)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| LMArena Longer Query | 1317 | 1254 |
Writing & Preference Too close to call
Gemma 3 12B: 47.7 (#205), GPT-4 Turbo: 47.9 (#201)
| Benchmark | Gemma 3 12B | GPT-4 Turbo |
|---|---|---|
| LMArena Text | 1334 | 1272 |
| LMArena Creative Writing | 1331 | 1269 |
| LMArena Multi-Turn | 1334 | 1267 |
| EQ-Bench Creative Writing | 1126 | — |
Frequently asked questions
Is Gemma 3 12B better than GPT-4 Turbo?
Gemma 3 12B is the stronger model overall, scoring 31.8 to 30.3 on the Noometry Index.
Which is cheaper, Gemma 3 12B or GPT-4 Turbo?
Gemma 3 12B is cheaper. It lists at $0.05 per million input tokens and $0.15 per million output tokens; GPT-4 Turbo lists at $10 and $30.
Is Gemma 3 12B or GPT-4 Turbo better for coding?
GPT-4 Turbo scores higher on coding benchmarks: 33.4 versus 31.2 in the Noometry coding category.
Which has the bigger context window?
Gemma 3 12B does, with 131K tokens against 128K.
How many benchmarks do Gemma 3 12B and GPT-4 Turbo share?
18 benchmarks have published results for both models. Gemma 3 12B has 24 scored results on Noometry and GPT-4 Turbo has 36.