LiquidAI/LFM2.5-1.2B-Instruct-MLX-4bit

Name: LiquidAI/LFM2.5-1.2B-Instruct-MLX-4bit
Author: LiquidAI

Run locally on Apple devices with Mirai

Type: local
From: LiquidAI
Quantization: MLX 4-bit
Parameters: 1.2B
Size: 632.8 MB
Source

Liquid AI

LFM2.5-1.2B-Instruct-MLX-4bit is a compact, quantized version of Liquid AI's LFM2.5-1.2B-Instruct model, exported specifically for fast inference on Apple Silicon devices using the MLX framework. At just 628 MB on disk, it delivers a remarkably efficient edge-deployment option for multilingual text generation.

Architecture & Specifications

This is a 4-bit quantized export (group size 64) of the 1.2-billion-parameter LFM2.5 instruction-tuned model. Despite its small footprint, it supports a generous 128K token context length, making it well-suited for tasks that require processing or generating long-form content on local hardware.

Multilingual Capability

LFM2.5-1.2B supports ten languages out of the box: English, Japanese, Korean, French, Spanish, German, Italian, Portuguese, Arabic, and Chinese — providing broad multilingual coverage for an edge-class model.

Ideal Use Cases

On-device chat and instruction following on MacBooks, iMacs, and other Apple Silicon machines
Low-latency local inference where cloud connectivity is unavailable or undesirable
Multilingual text generation for lightweight assistants and embedded applications
Long-context workloads that benefit from the 128K context window without requiring a large GPU

Getting Started

The model integrates directly with the `mlx-lm` Python library. Liquid AI recommends conservative sampling parameters — low temperature (0.1), top-k of 50, top-p of 0.1, and a slight repetition penalty of 1.05 — to produce focused, high-quality outputs.

Provenance

Developed by Liquid AI and derived from the base LFM2.5-1.2B-Instruct model. Released under the LFM 1.0 License.

Explore all local models

Choose framework

Run the following command to install Mirai SDK

spm https://github.com/trymirai/uzu.git

Apply code

1import Uzu23public func runChat() async throws {4    let engineConfig = EngineConfig.create()5    let engine = try await Engine.create(config: engineConfig)67    guard let model = try await engine.model(identifier: "LiquidAI/LFM2.5-1.2B-Instruct-MLX-4bit") else {8        return9    }10    for try await update in try await engine.download(model: model).iterator() {11        print("Download progress: \(update.progress())")12    }1314    let messages = [15        ChatMessage.system().withText(text: "You are a helpful assistant"),16        ChatMessage.user().withText(text: "Tell me a short, funny story about a robot")17    ]18    let session = try await engine.chat(model: model, config: .create())19    let stream = await session.replyWithStream(input: messages, config: .create())20    var message: ChatMessage? = nil21    for try await update in stream.iterator() {22        switch update {23        case .replies(let replies):24            message = replies.last?.message25        case .error(let error):26            print("Error: \(error)")27        }28    }29    print("Text: \(message?.text() ?? "empty")")30}

1Choose framework

2Run the following command to install Mirai SDK

spm https://github.com/trymirai/uzu.git

3Apply code

1	import Uzu
2
3	public func runChat() async throws {
4	let engineConfig = EngineConfig.create()
5	let engine = try await Engine.create(config: engineConfig)
6
7	guard let model = try await engine.model(identifier: "LiquidAI/LFM2.5-1.2B-Instruct-MLX-4bit") else {
8	return
9	}
10	for try await update in try await engine.download(model: model).iterator() {
11	print("Download progress: \(update.progress())")
12	}
13
14	let messages = [
15	ChatMessage.system().withText(text: "You are a helpful assistant"),
16	ChatMessage.user().withText(text: "Tell me a short, funny story about a robot")
17	]
18	let session = try await engine.chat(model: model, config: .create())
19	let stream = await session.replyWithStream(input: messages, config: .create())
20	var message: ChatMessage? = nil
21	for try await update in stream.iterator() {
22	switch update {
23	case .replies(let replies):
24	message = replies.last?.message
25	case .error(let error):
26	print("Error: \(error)")
27	}
28	}
29	print("Text: \(message?.text() ?? "empty")")
30	}