mlx-optiq
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lfm2-5-8b-a1b-optiq-5bpw-mlx

LiquidAI/LFM2.5-8B-A1B, quantized with OptiQ by sahilchachra for Apple Silicon; mixture-of-experts.

communityMoE
On disk8.9 GB
Memoryabout 12 GB

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 sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

OptiQ Code

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

optiq serve --model sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx
optiq code

OptiQ Lab

optiq lab --model sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

Claude Code

optiq run claude -m sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

Codex

optiq run codex -m sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

OpenCode

optiq run opencode -m sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

Mistral Vibe

optiq run vibe -m sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

Hermes Agent

optiq run hermes -m sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

OpenClaw

optiq run openclaw -m sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx

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("sahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx")
print(generate(model, tokenizer, prompt="Hello", max_tokens=256))

Details

FamilyLFM2.5 · LFM2.5 docs
ArchitectureLFM2 MoE
Base modelLiquidAI/LFM2.5-8B-A1B
Size on disk8.9 GB
Memory neededabout 12 GB
Imagesno, text only
Downloads20 in the last month
Updated2026-05-29
Hugging Facesahilchachra/lfm2-5-8b-a1b-optiq-5bpw-mlx