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Gemma 4 31B
Google's largest Gemma 4 model. Dense, multimodal and Apache 2.0 licensed, and a comfortable fit on one 48 GB GPU.
chatvisionmultilingual
Overview
Gemma 4 31B is the dense flagship of Google's Gemma 4 family, instruction tuned and able to take image input. It has a 262,144 token context window.
Hardware fit
Q4_K_M is 18.3 GB and Q8_0 is 33.2 GB. A 48 GB card such as an L40S runs Q8_0 with room for context, and a 24 GB card runs Q4_K_M with a shorter context. Vision input needs the separate mmproj file from the GGUF repo.
| Quantization | Weights |
|---|---|
| Q4_K_M | 18.3 GB |
| Q6_K | 25.2 GB |
| Q8_0 | 33.2 GB |
Sizes are the GGUF file sizes from unsloth/gemma-4-31B-it-GGUF. Budget extra VRAM for the KV cache, which grows with context size and parallel requests.
Deploying on Loadcore
- In the console, open Models and search for
unsloth/gemma-4-31B-it-GGUF. - Pick the quantization that fits the target server and start the download.
- Start an instance with the context size you need and GPU layers set to offload the full model.
- Point your tools at
http://your-server:9090/v1with your personal key.
Recommended settings
| Parameter | Value |
|---|---|
| temperature | 1.0 |
| top_p | 0.95 |
| top_k | 64 |
| repeat_penalty | 1.0 |
| min_p | 0.0 |
Values below are Google's recommended defaults from the model card.
Source: google/gemma-4-31B-it.