OptiQ

OptiQ is a local LLM stack for Apple Silicon that lets users quantize, prune, fine-tune, and serve models.

OptiQ is an MLX-native toolkit designed to run, quantize, prune, fine-tune, and serve large language models locally on Apple Silicon from M1 to M5. It uses sensitivity-driven mixed-precision quantization to shrink open models down to fit within a Mac's unified memory while preserving quality compared to uniform 4-bit quants. The software includes a command-line interface, a local web workbench called OptiQ Lab for chat and dataset design, a terminal coding agent, and an OpenAI and Anthropic compatible server. It supports various model families such as Qwen, Gemma, Mistral, and Nemotron. Users can also utilize OptiQ Cloud to route difficult turns to frontier models without changing plugins.

OptiQ at a glance

Best for: Software engineer
Runs on: macOS, CLI, Web, self-hosted, API
Pricing: Free to start with 20 Boosts; additional Boosts available.
Released: June 2026
Category: AI coding tool
Website: mlx-optiq.com

Key features

Sensitivity-driven mixed-precision quantization
LoRA fine-tuning and SFT/DPO support
OpenAI and Anthropic compatible local server
OptiQ Lab browser-based model workbench
Terminal coding agent for offline editing
OptiQ Cloud frontier model routing
KV-cache serving and speculative decoding

Use it for

Quantizing large language models to fit local Mac memory
Fine-tuning models locally using LoRA
Running a local coding agent in the terminal
Serving models via OpenAI and Anthropic compatible APIs
Chatting with models using a local web UI

Alternatives to OptiQ

MTPLX — It runs local models twice as fast via native MTP speculative decoding.
MLX LM — Runs LLMs and fine-tuning natively on Apple silicon hardware.
oMLX — It uses paged SSD KV caching to reduce agent TTFT to under 5 seconds.
Soup — Fine-tune and align models like Llama-3.1-8B on a 4 GB laptop GPU.
Strata — Runs large AI models locally on consumer gaming PCs without server reliance.
OpenCode — Works with 75+ model providers, local models, and existing subscriptions
Opik — It offers comprehensive tracing, automated evaluations, and open-source flexibility.
OptiLLM — Increases LLM reasoning accuracy by up to 10x without model training.
Optimum — It maximizes efficiency to train and run models on targeted hardware.
SmallCode — Runs fully local with budget-managed context and a forgiving parser for small models.
LMDeploy — Accelerates inference with high-performance engines and quantization tools.
iwant — Spins up cloud GPUs and open models instantly via a single command.

All OptiQ alternatives