gemma-2-27b-it: benchmark scores, price and ranking
gemma-2-27b-it from Google DeepMind ranks #662 of 743 LLMs on the LLMs Tiger aggregate benchmark score (43.8), based on 2 benchmark results captured up to 2026-10-13.
- Organisation
- Google DeepMind
- Type
- Open-weight / local model
- Open weights
- Yes
- Released
- 2024-06-24 (source: epoch)
- Cheapest API price
- $0.800 in / $0.800 out per million tokens (via together_ai, observed 2026-10-13T20:47Z)
- Aggregate rank
- #662 of 743 (score 43.8)
Across the 2 benchmarks where at least ten models are scored, gemma-2-27b-it is in the top 10% on 0 and in the top half on 0.
Its cheapest listed input price, $0.800 per million tokens, is lower than that of 38% of the 427 models with a listed price.
gemma-2-27b-it benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| GPQA Diamond | 36.5% | #231 of 275 | Epoch AI Benchmarking Hub | 2026-10-13 |
| OTIS Mock AIME | 1.4% | #178 of 189 | Epoch AI Benchmarking Hub | 2026-10-13 |
About gemma-2-27b-it
gemma-2-27b-it is an open-weight model that can run on your own hardware from Google DeepMind. It was released on 2024-06-24, according to Epoch AI. The cheapest API listing we track charges $0.800 per million input tokens and $0.800 per million output tokens, through together_ai. We hold 2 benchmark results for it across 1 area, and none is in the top tenth of its board.
Where gemma-2-27b-it stands
On our aggregate score, gemma-2-27b-it is #662 of 743 ranked models, in the lower half. Its score is 43.8; the scale is centred on 50, so it sits 6.2 points below the typical model. That beats 11% of the ranked field. Among the 41 ranked Google DeepMind models it is #31. The next one up is gemini-1.5-pro-002 at 43.9. The next one down is gemma-2-27b at 43.7.
gemma-2-27b-it, benchmark by benchmark
GPQA Diamond is a weak spot. gemma-2-27b-it scores 36.5%, #231 of 275, behind 84% of the models measured. The leader, GPT-6 Astra (max), reaches 95.8%. It covers expert-level science questions. The board median is 71.7%, so gemma-2-27b-it is 35.2 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
OTIS Mock AIME is a weak spot. gemma-2-27b-it scores 1.4%, #178 of 189, behind 94% of the models measured. The leader, Claude Fable 5.1 (max), reaches 100.0%. It covers competition maths (AIME 2024-25 style). The board median is 57.8%, so gemma-2-27b-it is 56.4 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Strengths and weaknesses
Reasoning, maths and science: weak, ahead of 11% of the field on average across 2 benchmarks. Its best board here is GPQA Diamond (#231 of 275) and its weakest is OTIS Mock AIME (#178 of 189).
Price and value
The median input price across the 427 priced models is $0.500 per million tokens, so gemma-2-27b-it costs more than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on qwen2-72b-instruct ($0.900) and claude-haiku-4-5-20251001 ($1.00).
Release history
The Google DeepMind model released before it was gemma-2-27b on 2024-06-24, which scores 43.7. The next one was Gemma 2 9B on 2024-06-24, at 46.5.
Reading these numbers
The 2 scores on this page come from 1 source: Epoch AI Benchmarking Hub (2). No official leaderboard supplied any of them, so treat them as third-party measurements. With 2 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #659 Qwen2-7B (43.9)
- #660 gemini-1.5-pro-002 (43.9)
- #661 GPT-5 nano (high) (43.8)
- #663 Magistral Small 1.2 (43.8)
- #664 GPT-4 (Mar 2023) (43.7)
- #665 gemma-2-27b (43.7)
More from Google DeepMind
- Gemini 3.8 Flash (high) (#26, 54.0)
- Gemini 3.7 Flash (high) (#27, 53.9)
- Gemini 3 Pro Preview (#31, 53.7)
- Gemini 3 Deep Think (#60, 52.6)
- AI co-mathematician (#69, 52.3)
- Gemini 3 Flash (#120, 51.5)
Compare it on the live leaderboard → · How the aggregate score works