Model comparison
Gemma 3 27B vs GPT-5.2 Pro
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 30.8 on the Noometry Index. Gemma 3 27B costs 578× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
GoogleSummary
- They share 1 benchmark with published results for both. Gemma 3 27B scores higher in 0 categories and GPT-5.2 Pro in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.2 Pro leads 65.3 to 25.9.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- GPT-5.2 Pro 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-5.2 Pro | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 30.8 | 52.3 |
| Released | 2025-03-11 | 2025-12-11 |
| Weights | Open | Proprietary |
| Context window | 131K | 400K |
| Max output | 8K | 128K |
| Input $ / M tokens | $0.08 | $21 |
| Output $ / M tokens | $0.16 | $168 |
| Results tracked | 43 | 8 |
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Category by category
Coding Not comparable
Gemma 3 27B: 22.5 (#334), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| Aider Polyglot | 4.9% | — |
| SciCode | 21.2% | — |
| LiveBench Coding | 39.9% | — |
| LMArena Coding | 1322 | — |
Agentic & Tool Use Not comparable
Gemma 3 27B: 25.1 (#110), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | — |
Reasoning GPT-5.2 Pro leads
Gemma 3 27B: 16.7 (#301), GPT-5.2 Pro: 51.5 (#33)
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| Epoch Capabilities Index | 130.04 | 155.4 |
| ARC-AGI-2 | — | 54.2% |
| SimpleBench | — | 57.4% |
| Kagi LLM Benchmark | 40.4% | — |
| NYT Connections (extended) | — | 79.3% |
| ARC-AGI-1 | — | 90.5% |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 43.8% | — |
| LMArena Hard Prompts | 1340 | — |
| DTBench | 52.5% | — |
| LiveBench Data Analysis | 51.5% | — |
| LMCA | 12.3% | — |
| LiveBench | 50% | — |
Math GPT-5.2 Pro leads
Gemma 3 27B: 25.9 (#265), GPT-5.2 Pro: 65.3 (#29)
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 74% |
| FrontierMath Tier 4 | — | 46% |
| OTIS Mock AIME 2024-2025 | 22.5% | — |
| LiveBench Math | 55.4% | — |
| LMArena Math | 1312 | — |
| MATH Level 5 | 74% | — |
| FrontierMath Tier 4 (v1) | — | 31.3% |
Knowledge Not comparable
Gemma 3 27B: 25.5 (#261), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| GPQA Diamond | 47.7% | — |
| Confabulations | 40.3% | — |
| Vectara Hallucination Rate | 7.4% | — |
| LMArena Expert | 1304 | — |
Multimodal Not comparable
Gemma 3 27B: 32.6 (#100), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| LMArena Vision | 1164 | — |
| GeoBench | 52% | — |
Multilingual Not comparable
Gemma 3 27B: 46.9 (#155), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| LMArena Non-English | 1334 | — |
| LMArena Chinese | 1346 | — |
| LMArena French | 1368 | — |
| LMArena German | 1362 | — |
| LMArena Japanese | 1287 | — |
| LMArena Korean | 1308 | — |
| LMArena Russian | 1349 | — |
| LMArena Spanish | 1349 | — |
Instruction Following Not comparable
Gemma 3 27B: 70.6 (#160), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| LiveBench Instruction Following | 74.9% | — |
| LMArena Instruction Following | 1321 | — |
Long Context Not comparable
Gemma 3 27B: 27.6 (#293), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| Fiction.LiveBench | 33.3% | — |
| LMArena Longer Query | 1333 | — |
Writing & Preference Not comparable
Gemma 3 27B: 52.5 (#168), GPT-5.2 Pro: —
| Benchmark | Gemma 3 27B | GPT-5.2 Pro |
|---|---|---|
| LMArena Text | 1358 | — |
| LMArena Creative Writing | 1346 | — |
| Short-Story Creative Writing | 79.9% | — |
| EQ-Bench Creative Writing | 1266 | — |
| LMArena Multi-Turn | 1345 | — |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than GPT-5.2 Pro?
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 30.8 on the Noometry Index. Gemma 3 27B costs 578× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 27B or GPT-5.2 Pro?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; GPT-5.2 Pro lists at $21 and $168.
Which has the bigger context window?
GPT-5.2 Pro does, with 400K tokens against 131K.
How many benchmarks do Gemma 3 27B and GPT-5.2 Pro share?
1 benchmark has published results for both models. Gemma 3 27B has 43 scored results on Noometry and GPT-5.2 Pro has 8.