mlx-community/LFM2-1.2B-4bit
Run locally on Apple devices with Mirai
- Type
- local
- From
- LiquidAI
- Quantization
- MLX 4-bit
- Parameters
- 1.2B
- Size
- 632.8 MB
A 4-bit quantized version of LiquidAI's LFM2-1.2B, converted to Apple's MLX format for efficient on-device inference on Apple Silicon hardware. This community conversion was produced using `mlx-lm` v0.26.0.
Origin & Architecture
LFM2-1.2B is developed by Liquid AI as part of their LFM2 (Liquid Foundation Model 2) family. Designed specifically for edge deployment, the 1.2-billion-parameter model delivers capable text generation in a compact footprint. The 4-bit quantization further reduces memory requirements, making it well-suited for local inference on MacBooks and other Apple Silicon devices without requiring cloud resources.
Multilingual Support
The model supports eight languages out of the box: English, Arabic, Chinese, French, German, Japanese, Korean, and Spanish — giving it broad multilingual coverage despite its small size.
Key Highlights
- Edge-optimized: Built from the ground up for low-resource environments, balancing quality and efficiency at 1.2B parameters.
- 4-bit quantization: Significantly reduced memory usage compared to full-precision weights, enabling fast inference on consumer hardware.
- MLX-native: Runs through the `mlx-lm` library, taking full advantage of Apple's MLX framework for unified memory and GPU acceleration on M-series chips.
- Chat-ready: Includes a chat template, supporting conversational use cases directly.
Use Cases
LFM2-1.2B-4bit is a strong choice for developers building local AI-powered applications on macOS — including chatbots, writing assistants, multilingual text generation, and lightweight reasoning tasks — where privacy, latency, and offline capability matter more than peak benchmark performance.
License: LFM 1.0 (custom Liquid AI license) Base model: LiquidAI/LFM2-1.2B
spm https://github.com/trymirai/uzu.git
| 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: "mlx-community/LFM2-1.2B-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 | } |