mlx-optiq
OptiQ Lab · local workbench

Your models, in a local web app.

A local web app for the whole workflow: chat with your models, run deep research on them, quantize new ones, fine-tune with your data, split a big model across several Macs, and compare them side by side. It runs on your Mac; nothing is uploaded.

localhost:8080 · OptiQ Lab
$ optiq lab
The workbench

The full OptiQ workflow, in a browser.

The same MLX-native engine as the CLI, wrapped in a local web app. Pick a model from the Hub, chat with it, quantize your own, fine-tune on your data, and compare two models side by side.

Chat

Chat with tools

Talk to any served model with sandboxed web search, Python, and terminal tools, plus image upload and chat-with-files retrieval with citations.

Arena

Model Arena

Run two models on the same prompt and compare speed and output.

Hub

Model Hub

Browse the published OptiQ quants, search Hugging Face, and load a model with one click, straight into the Lab.

Quantize

Quantize wizard

Point it at any Hugging Face model and get a sensitivity-driven mixed-precision quant, with a live view of the per-layer bit allocation.

Fine-tune

SFT & DPO

Fine-tune with sensitivity-aware LoRA, SFT or DPO, on your own dataset, all local, with progress and loss curves in the browser.

Dataset

Dataset designer

Build and shape a training set from files and templates before you fine-tune, without leaving the app.

Deep research

Research reports, from your own model.

Ask a hard question and the Lab drafts a report, finds the gaps in it, searches the web to fill them, and revises, over several rounds. Every claim points to a page it actually read, and the whole thing runs on the local model you serve.

01

Draft, then dig. It writes a rough answer first, then treats its own gaps as the search plan, so later rounds chase what is missing instead of repeating what it already has.

Iterative
02

Evidence first. Findings are tied to pages the model retrieved and read, and the report ends with the sources, so you can check the claim rather than trust it.

Grounded
03

Nothing leaves the Mac. The model, the reasoning, and the report all stay local. Only the web searches go out, to the engine you choose.

Private
Cluster

Run one model across several Macs.

Link two or more Apple Silicon Macs over Thunderbolt and the Lab serves a single model pipeline-parallel across the ring, so a model too large for any one machine runs on the group. A live topology view shows the nodes, and the Lab chat points straight at the cluster endpoint.

Discover

Thunderbolt ring

Nodes find each other over the Thunderbolt bridge and form a ring. The panel draws the live topology as peers join.

Serve

Pipeline-parallel

The model's layers are split across the machines, so combined memory, not one Mac's ceiling, sets how big a model you can run.

Use

One endpoint

The ring exposes a single server. Point the Lab chat, OptiQ Code, or any OpenAI-compatible client at it.

How it connects The Lab drives the same optiq engine as the CLI and serves over the same dual-protocol server, so a model you serve in the Lab is the one OptiQ Code can drive. See the Lab docs.

A local AI workbench in one install.

Run, quantize, fine-tune, and compare models on your own Mac.