Google · open-weights model
gemma-2-27b-it
gemma-2-27b-it is a 27.2B-parameter model by Google. Its smallest quant (Q4_K_M) needs at least 18.7GB of GPU-addressable memory at 8K context; it loads cleanly at a quality quant on 20 of the 50 machines we track.
- Parameters
- 27.2B
- Layers
- 46
- Max context
- 8K
- Attention
- SLIDING-WINDOW
- License
- gemma
Config from google/gemma-2-27b-it
Quants and what they need
Measured file sizes; “needs” = weights + KV cache at 8K context + overhead.
| Quant | File size | Needs ≥ |
|---|---|---|
| Q8_0 | 28.9 GB | 31.0 GB |
| Q6_K | 22.3 GB | 24.4 GB |
| Q5_K_M | 19.4 GB | 21.5 GB |
| Q4_K_M | 16.6 GB | 18.7 GB |
What runs gemma-2-27b-it
Every machine we track, graded at its best clean-fit quant.
Verdicts computed from published specs and measured GGUF sizes — how the math works.