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Local LLM Guide

Model

Gemma 3 27B Instruct

Start with a supported compressed build and short context. 64GB RAM estimate. Best use: highest-quality Gemma 3 local chat

27BMultimodal

Best use

highest-quality Gemma 3 local chat · multimodal reasoning

Memory planning

64GB RAM estimate

Expected pace

Depends on your hardware, app, and conversation length

License

Gemma Terms of Use; read the model’s terms before use

Who should use this model?

  • highest-quality Gemma 3 local chat
  • multimodal reasoning
  • long-context work
  • workstation inference

Choose something else when

  • less than 32GB system RAM is available
  • less than 24GB VRAM is available
  • low latency is required

What hardware makes sense?

The download is only part of the memory needed. Leave room for the app, the input it processes, and other open programs. For chat models, context includes the instructions, conversation, and answer. Longer context needs more memory.

CPU only
Memory or response time may limit use. Try a smaller model first.
8GB system memory
Use a smaller model for this memory limit.
16GB system memory
Use a smaller model for this memory limit.
32GB system memory
Memory or response time may limit use. Try a smaller model first.
8GB GPU memory
Use a smaller model for this memory limit.
12GB GPU memory
Use a smaller model for this memory limit.
24GB GPU memory
Memory or response time may limit use. Try a smaller model first.
Apple unified memory
Memory or response time may limit use. Try a smaller model first.

Model facts that change the decision

Parameters
27B
Input
Text · Image · Video
Published context limit
131,072 tokens
Model format
safetensors · GGUF · Ollama · Transformers · Kaggle
Suggested compression
Q4_K_M for default local use; Q5_K_M if the model and multimodal projection fit comfortably in RAM/VRAM.
Typical Q4 file
16.55GB before runtime and context overhead
Languages
English · 140+ languages

Using image input

This model needs an app or library that supports its image-processing components. Follow the exact model’s instructions for preparing image inputs. Some GGUF downloads also need a matching projector file; loading the text model alone does not establish image support.

First setup

Ollama

ollama run gemma3:27b

LM Studio: Search for bartowski/google_gemma-3-27b-it-GGUF and verify image/mmproj support before enabling vision.

llama.cpp

Use hf.co/bartowski/google_gemma-3-27b-it-GGUF:Q4_K_M plus the matching mmproj file for image input.

Conditions that change the answer

  • Video understanding is described by Google for Gemma 3 generally, but local GGUF/Ollama support should be treated as runner-dependent.
  • GGUF files are community conversions, not official Google GGUF releases.
  • The download size includes the Q4_K_M model plus a matching multimodal projection file where applicable.
  • Allow memory for the model file, the app, and your conversation.

Read the controlling license text →