Head to head
Gemma 2 27B vs Gemma 3 27B
Gemma 2 27B from Google DeepMind against Gemma 3 27B from Google DeepMind — specification, price and every benchmark both makers have published, in one table.
Benchmarks
Gemma 3 27B leads
Gemma 3 27B wins 3 of the 3 benchmarks both models report, Gemma 2 27B wins 0, by a wide margin. The average gap across shared tests is 55.2 points.
Price
Gemma 3 27B is cheaper
On a 3:1 input-to-output mix, Gemma 3 27B costs $0.125 per million tokens against $0.27 for Gemma 2 27B — about 2.2× less.
What actually differs
- Gemma 3 27B takes 131K tokens of context against 8.2K — 16.0× more room for long documents or a large codebase.
- Only Gemma 3 27B reads images. If your input includes screenshots, charts or documents, that decides it.
Scorecard
Which is better at what
Maths, coding, reasoning and the rest — one line each, averaged over the benchmarks both models actually report.
| Category | Gemma 2 27B | Gemma 3 27B | Better at this |
|---|---|---|---|
| ReasoningOnly one model reports this | — | — | Not comparable |
| MathsNeither model reports this | — | — | Not comparable |
| CodingHumanEval | 51.8% | 87.8% | Gemma 3 27B+36.0 |
| KnowledgeMMLU-Pro | 56.0% | 67.5% | Gemma 3 27B+11.5 |
| MultimodalOnly one model reports this | — | — | Not comparable |
| Instruction followingNeither model reports this | — | — | Not comparable |
| Human preferenceLMArena Elo | 1220 | 1338 | Gemma 3 27B+118 |
| Categories wonOut of 3 comparable | 0 | 3 | Gemma 3 27B |
Each category averages only the benchmarks every model here reports, so no one is credited for a test the other did not run. A category with no shared test is marked Not comparable rather than guessed at.
Side by side
Gemma 2 27B and Gemma 3 27B, row by row
| Attribute | Gemma 2 27BGoogle DeepMind | Gemma 3 27BGoogle DeepMind |
|---|---|---|
| Specification | ||
| MakerWho built it | Google DeepMind | Google DeepMind |
| Released | 2024-06 | 2025-03 |
| ParametersTotal, and active per token for a mixture of experts | 27B | 27B |
| Architecture | Dense transformer | Dense transformer |
| Context windowHow much can go in at once | 8,192 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 8,192 tokens |
| Input | Text | Text, Image |
| ReasoningSpends extra tokens thinking before it answers | No | No |
| Tool calling | No | Yes |
| Licence | Gemma Terms of Use | Gemma Terms of Use |
| Open weightsCan you download and run it yourself | Yes | Yes |
| Price | ||
| Input priceUSD per million tokens in | $0.27 | $0.10 |
| Output priceUSD per million tokens out | $0.27 | $0.20 |
| Blended 3:1A 3-in-to-1-out million-token mix — a fairer single number than input price alone | $0.27 | $0.125Cheapest |
| Price note | Open weights — this is a representative hosting rate, not a first-party price. Running it yourself costs only hardware. | Open weights — this is a representative hosting rate, not a first-party price. Running it yourself costs only hardware. |
| Published benchmarks | ||
| MMLU-Pro12,000 reasoning-heavy multiple-choice questions across 14 academic subjects, with ten options instead of four. The harder successor to MMLU. | ||
| GPQA Diamond198 graduate-level physics, chemistry and biology questions written to be Google-proof. PhD holders in the matching field score about 65%. | Not reported | |
| HumanEval164 short Python functions written from a docstring. Saturated at the frontier — kept here for continuity with older models. | ||
| MMMUCollege-level questions that require reading charts, diagrams, tables and photographs alongside the text. | Not reported | |
| LMArena EloElo rating from blind pairwise votes by the public on LMArena. Measures what people prefer, not what is correct. | ||
| Links | Hugging Face · Full page | Hugging Face · Full page |
| Row verified | 2026-08 | 2026-08 |
Where these numbers come from
Every score on this page is a published figure, taken from the model's own card, system card, technical report or release post, or from a public leaderboard. CorX Labs did not run these evaluations. Most are self-reported by the lab that built the model, which means they were produced under that lab's own choice of prompt, scaffold and number of attempts — so treat them as a starting point for a shortlist, not as a settled ranking.
A score someone other than the model's maker measured is marked Independent and names its measurer. Those are the stronger numbers on this page — an outside harness has no reason to flatter anyone — and there are not many of them.
Where a figure has not been published, the cell reads Not reported rather than an estimate. Nothing here is inferred, interpolated or guessed. Each model records the month its row was last checked. Full method and caveats.
Questions
Gemma 2 27B or Gemma 3 27B?
Is Gemma 2 27B better than Gemma 3 27B?
Gemma 3 27B wins 3 of the 3 benchmarks both models report, Gemma 2 27B wins 0, by a wide margin. The average gap across shared tests is 55.2 points.
Which is cheaper, Gemma 2 27B or Gemma 3 27B?
On a 3:1 input-to-output mix, Gemma 3 27B costs $0.125 per million tokens against $0.27 for Gemma 2 27B — about 2.2× less.
What is the difference between Gemma 2 27B and Gemma 3 27B?
Gemma 3 27B takes 131K tokens of context against 8.2K — 16.0× more room for long documents or a large codebase. Only Gemma 3 27B reads images. If your input includes screenshots, charts or documents, that decides it.
