Gemma 2 27B
Gemma 2 27B — Google large language model (2024) with a 8K-token context window and an MMLU score of 75.2%, released with open weights.
Key specifications
| MMLU (capability) | 75.2% |
|---|---|
| Context window (K tokens) | 8 |
| Input price ($/1M) | 0 |
| Output price ($/1M) | 0 |
About Gemma 2 27B
The Gemma 2 27B is a large language model from Google with a 8K-token context window and an MMLU score of 75.2%. It is open weights, so it can be self-hosted. MMLU measures general knowledge and reasoning; real-world quality also depends on coding, tool use, latency and safety.
The comparisons below show how Gemma 2 27B stacks up against the alternatives people most often weigh against it, with the specific numbers laid out side by side.
Frequently asked questions
Is the Gemma 2 27B any good?
Gemma 2 27B — Google large language model (2024) with a 8K-token context window and an MMLU score of 75.2%, released with open weights.
What are the key specs of the Gemma 2 27B?
See the specification table above for the full breakdown.