Who should use this model?
- very small local chat
- fast offline assistants
- classification
- edge experimentation
Choose something else when
- image input is required
- higher answer quality is required
- large-document synthesis 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
- A possible starting point with a compressed model and short conversation; check the exact file size.
- 8GB system memory
- A possible starting point with a compressed model and short conversation; check the exact file size.
- 16GB system memory
- A possible starting point with a compressed model and short conversation; check the exact file size.
- 32GB system memory
- A possible starting point with a compressed model and short conversation; check the exact file size.
- 8GB GPU memory
- A possible starting point with a compressed model and short conversation; check the exact file size.
- 12GB GPU memory
- A possible starting point with a compressed model and short conversation; check the exact file size.
- 24GB GPU memory
- A possible starting point with a compressed model and short conversation; check the exact file size.
- Apple unified memory
- A possible starting point with a compressed model and short conversation; check the exact file size.
Model facts that change the decision
- Parameters
- 1B
- Input
- Text
- Published context limit
- 32,768 tokens
- Model format
- safetensors · GGUF · Ollama · Transformers · Kaggle
- Suggested compression
- Q4_K_M for default local use; Q5_K_M if the model still fits comfortably in RAM/VRAM.
- Typical Q4 file
- 0.806GB before runtime and context overhead
- Languages
- English · 140+ languages
First setup
Ollama
ollama run gemma3:1bLM Studio: Search for bartowski/google_gemma-3-1b-it-GGUF and select Q4_K_M or Q5_K_M.
llama.cpp
Use hf.co/bartowski/google_gemma-3-1b-it-GGUF:Q4_K_M; increase context only if memory permits.
Conditions that change the answer
- The generic Gemma 3 model card describes image input, but Ollama's local 1B tag is text-only and Gemma 3 local vision entries start at 4B; use the 1B package for text only.
- GGUF files are community conversions, not official Google GGUF releases.
- Allow memory for the model file, the app, and your conversation.
Read the controlling license text →