gemma-4-31B-it-qat-OptiQ-4bit
google/gemma-4-31B-it-qat-q4_0-unquantized, quantized by OptiQ for Apple Silicon; takes images.
visionOn disk23.5 GB
Memoryabout 29 GB
Capability Score82.01
Imagesyes
Capability Score breakdown
The six metrics behind this model's Capability Score of 82.01, as reported in the model card. Values are compared with uniform 4-bit (QAT base).
- This model
- Uniform 4-bit (QAT base)
Use it
Install
pip install mlx-optiqServe it
An OpenAI- and Anthropic-compatible server on this Mac. Every app below can use it.
optiq serve --model mlx-community/gemma-4-31B-it-qat-OptiQ-4bitOptiQ Code
The terminal coding agent uses whatever model optiq serve is running.
optiq serve --model mlx-community/gemma-4-31B-it-qat-OptiQ-4bit
optiq codeOptiQ Lab
optiq lab --model mlx-community/gemma-4-31B-it-qat-OptiQ-4bitClaude Code
optiq run claude -m mlx-community/gemma-4-31B-it-qat-OptiQ-4bitCodex
optiq run codex -m mlx-community/gemma-4-31B-it-qat-OptiQ-4bitOpenCode
optiq run opencode -m mlx-community/gemma-4-31B-it-qat-OptiQ-4bitMistral Vibe
optiq run vibe -m mlx-community/gemma-4-31B-it-qat-OptiQ-4bitHermes Agent
optiq run hermes -m mlx-community/gemma-4-31B-it-qat-OptiQ-4bitOpenClaw
optiq run openclaw -m mlx-community/gemma-4-31B-it-qat-OptiQ-4bitoptiq run starts optiq serve if it is not running, sets the agent up for this session only, and stops the server when the agent exits.
mlx-lm, text only
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/gemma-4-31B-it-qat-OptiQ-4bit")
print(generate(model, tokenizer, prompt="Hello", max_tokens=256))Details
| Family | Gemma-4 · Gemma-4 docs |
|---|---|
| Architecture | Gemma 4 |
| Base model | google/gemma-4-31B-it-qat-q4_0-unquantized |
| Size on disk | 23.5 GB |
| Memory needed | about 29 GB |
| Images | yes, through optiq serve and the Lab |
| Capability Score | 82.01 (from the model card) |
| Downloads | 2,558 in the last month |
| Updated | 2026-10-18 |
| Hugging Face | mlx-community/gemma-4-31B-it-qat-OptiQ-4bit |