Model comparison
Gemma 3 27B vs GPT-5.3 Chat
GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 30.5 on the Noometry Index. Gemma 3 27B costs 48× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. Gemma 3 27B scores higher in 0 categories and GPT-5.3 Chat in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.3 Chat leads 40.8 to 22.1.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- Gemma 3 27B accepts more context: 131K tokens versus 128K.
- Gemma 3 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 27B | GPT-5.3 Chat | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 30.5 | 42.1 |
| Released | 2025-03-11 | 2026-03-03 |
| Weights | Open | Proprietary |
| Context window | 131K | 128K |
| Max output | 8K | 16K |
| Input $ / M tokens | $0.08 | $1.75 |
| Output $ / M tokens | $0.16 | $14 |
| Results tracked | 43 | 18 |
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Category by category
Coding GPT-5.3 Chat leads
Gemma 3 27B: 22.1 (#329), GPT-5.3 Chat: 40.8 (#124)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Coding | 1322 | 1408 |
| Aider Polyglot | 4.9% | — |
| SciCode | 21.2% | — |
| LiveBench Coding | 39.9% | — |
Agentic & Tool Use Not comparable
Gemma 3 27B: 24.9 (#105), GPT-5.3 Chat: —
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | — |
Reasoning GPT-5.3 Chat leads
Gemma 3 27B: 16.3 (#297), GPT-5.3 Chat: 27.3 (#105)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Hard Prompts | 1340 | 1399 |
| Kagi LLM Benchmark | 40.4% | — |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 43.8% | — |
| DTBench | 52.5% | — |
| LiveBench Data Analysis | 51.5% | — |
| LMCA | 12.3% | — |
| Epoch Capabilities Index | 130.04 | — |
| LiveBench | 50% | — |
Math GPT-5.3 Chat leads
Gemma 3 27B: 24.4 (#261), GPT-5.3 Chat: 35.4 (#146)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Math | 1312 | 1389 |
| OTIS Mock AIME 2024-2025 | 22.5% | — |
| LiveBench Math | 55.4% | — |
| MATH Level 5 | 74% | — |
Knowledge GPT-5.3 Chat leads
Gemma 3 27B: 25.4 (#256), GPT-5.3 Chat: 38.2 (#137)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Expert | 1303 | 1397 |
| GPQA Diamond | 47.7% | — |
| Confabulations | 40.3% | — |
| Vectara Hallucination Rate | 7.4% | — |
Multimodal Not comparable
Gemma 3 27B: 32.0 (#94), GPT-5.3 Chat: —
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Vision | 1165 | — |
| GeoBench | 52% | — |
Multilingual GPT-5.3 Chat leads
Gemma 3 27B: 47.0 (#150), GPT-5.3 Chat: 50.5 (#119)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Non-English | 1334 | 1383 |
| LMArena Chinese | 1347 | 1433 |
| LMArena French | 1368 | 1398 |
| LMArena German | 1362 | 1384 |
| LMArena Japanese | 1287 | 1351 |
| LMArena Korean | 1308 | 1347 |
| LMArena Russian | 1349 | 1400 |
| LMArena Spanish | 1348 | 1371 |
Instruction Following GPT-5.3 Chat leads
Gemma 3 27B: 70.8 (#155), GPT-5.3 Chat: 73.0 (#124)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Instruction Following | 1321 | 1378 |
| LiveBench Instruction Following | 74.9% | — |
Long Context GPT-5.3 Chat leads
Gemma 3 27B: 27.6 (#288), GPT-5.3 Chat: 42.6 (#115)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Longer Query | 1333 | 1396 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference GPT-5.3 Chat leads
Gemma 3 27B: 52.7 (#161), GPT-5.3 Chat: 63.3 (#65)
| Benchmark | Gemma 3 27B | GPT-5.3 Chat |
|---|---|---|
| LMArena Text | 1358 | 1389 |
| LMArena Creative Writing | 1346 | 1356 |
| EQ-Bench Creative Writing | 1266 | 1690 |
| LMArena Multi-Turn | 1344 | 1413 |
| Short-Story Creative Writing | 79.9% | — |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than GPT-5.3 Chat?
GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 30.5 on the Noometry Index. Gemma 3 27B costs 48× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 27B or GPT-5.3 Chat?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is Gemma 3 27B or GPT-5.3 Chat better for coding?
GPT-5.3 Chat scores higher on coding benchmarks: 40.8 versus 22.1 in the Noometry coding category.
Which has the bigger context window?
Gemma 3 27B does, with 131K tokens against 128K.
How many benchmarks do Gemma 3 27B and GPT-5.3 Chat share?
18 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and GPT-5.3 Chat has 18.