LiquidAI/LFM2.5-1.2B-Thinking

Name: LiquidAI/LFM2.5-1.2B-Thinking
Author: LiquidAI

Run locally on Apple devices with Mirai

Type: local
From: LiquidAI
Quantization: No
Parameters: 1.2B
Size: 2.2 GB
Source

LFM2.5-1.2B Benchmarks

LFM2.5-1.2B-Thinking is a compact reasoning model from Liquid AI, designed to bring high-quality AI inference to edge devices while running under 1GB of memory. Part of the LFM2.5 family, it builds on the LFM2 hybrid architecture with extended pre-training on 28 trillion tokens and multi-stage reinforcement learning.

Architecture & Specifications

The model features a hybrid design with 1.17B parameters across 16 layers — 10 double-gated LIV convolution blocks paired with 6 grouped-query attention (GQA) blocks. It supports a 32,768-token context window and a vocabulary of 65,536 tokens. Eight languages are supported: English, Arabic, Chinese, French, German, Japanese, Korean, and Spanish.

Liquid AI

Performance & Speed

LFM2.5-1.2B-Thinking rivals much larger models on reasoning benchmarks, achieving strong scores on MATH-500 (87.96), IFEval (88.42), and GSM8K (85.60). On hardware, it delivers 239 tok/s decode on AMD CPU and 82 tok/s on mobile NPU, making it practical for real-time on-device applications.

Recommended Use Cases

Liquid AI recommends this model for agentic tasks, data extraction, and RAG workflows. It also supports structured function calling with Pythonic tool-use syntax. It is less suited for knowledge-intensive tasks or programming.

Deployment Options

The model ships in multiple formats for flexible deployment: native Transformers/vLLM checkpoints, GGUF for llama.cpp and CPU inference, ONNX for cross-platform hardware acceleration, and MLX for Apple Silicon. It also works with LM Studio for local desktop use. Fine-tuning is supported via Unsloth and TRL with LoRA, SFT, DPO, and GRPO recipes.

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-Thinking") 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-Thinking") 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	}