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diffusiongemma-26B-A4B-it-OptiQ-4bit

google/diffusiongemma-26B-A4B-it, quantized by OptiQ for Apple Silicon; takes images.

vision

On disk17.8 GB

Memoryabout 22 GB

Capability Score68.25

Imagesyes

Capability Score breakdown

The six metrics behind this model's Capability Score of 68.25, as reported in the model card.

Use it

Install

pip install mlx-optiq

Serve it

An OpenAI- and Anthropic-compatible server on this Mac. Every app below can use it.

optiq serve --model mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

OptiQ Code

The terminal coding agent uses whatever model optiq serve is running.

optiq serve --model mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit
optiq code

OptiQ Lab

optiq lab --model mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

Claude Code

optiq run claude -m mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

Codex

optiq run codex -m mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

OpenCode

optiq run opencode -m mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

Mistral Vibe

optiq run vibe -m mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

Hermes Agent

optiq run hermes -m mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

OpenClaw

optiq run openclaw -m mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit

optiq 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/diffusiongemma-26B-A4B-it-OptiQ-4bit")
print(generate(model, tokenizer, prompt="Hello", max_tokens=256))

Details

Family	Diffusion LLM · Diffusion LLM docs
Architecture	DiffusionGemma
Base model	google/diffusiongemma-26B-A4B-it
Size on disk	17.8 GB
Memory needed	about 22 GB
Images	yes, through optiq serve and the Lab
Capability Score	68.25 (from the model card)
Downloads	661 in the last month
Updated	2026-07-20
Hugging Face	mlx-community/diffusiongemma-26B-A4B-it-OptiQ-4bit