LFM2.5 Thinking 1.2B

Overview

Liquid AI's 1.2B reasoning variant with an explicit thinking mode, sub-1GB Q4 footprint, and CPU/iGPU-friendly inference. 32k context.

When to pick this model

• On-device reasoning on laptops and SBCs without a discrete GPU
• Latency-sensitive tasks that still benefit from chain-of-thought
• Edge agents where memory budget rules out larger models
• Privacy-first deployments that must stay fully local

VRAM requirements by quantization

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

Strengths

• Negligible memory footprint — under 1GB at Q4
• Runs comfortably on CPU and integrated GPUs
• Explicit thinking mode for visible chain-of-thought
• Low-latency inference suitable for interactive use

Limitations

• 1.2B parameters cap absolute capability
• 32k context is short by 2026 standards
• LFM Open License rather than pure Apache

Architecture & training

Architecture: Liquid Foundation Model · 1.2B parameters · 32k context · thinking mode

Training: Liquid AI's LFM2.5 family. Reasoning variant with explicit chain of thought.

Quick start

ollama run lfm2.5-thinking

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.