Overview

FreeToken democratizes large language model (LLM) deployment by bringing datacenter-scale Mixture-of-Experts (MoE) serving capabilities directly to your desktop. It empowers users to run massive, frontier-grade open-weight models locally on consumer hardware, achieving blazing-fast, interactive speeds. By intelligently managing heterogeneous edge resources like GPUs, CPUs, and host memory, FreeToken transforms your existing hardware into a powerful, elastic inference platform.

Key Features

• Edge-Native Runtime for MoE: Experience highly efficient MoE inference with advanced techniques including bandwidth-adaptive CPU-GPU co-execution, full-layer prefill streaming, global expert caching, and the innovative FTW fast weight format.
• Semantic-Aware Caching: Smartly manages recurrent state and KV caches with semantic checkpoints, enabling efficient context editing for agentic workflows without costly recomputation.
• Elastic Memory Management: Dynamically reallocate VRAM between expert caches and KV memory at runtime, eliminating the need for engine restarts or weight reloads.
• Broad Model and Ecosystem Support: Run a wide array of frontier MoE models (e.g., DeepSeek-V4-Flash, Qwen3.6-35B-A3B) in various quantization formats. Offers Anthropic/OpenAI-compatible APIs for seamless integration with popular coding and tool-calling agents.
• Consumer Hardware Compatibility: Designed to scale across laptops, gaming desktops, and workstations, with native support for NVIDIA RTX 30, 40, and 50 series GPUs.

Typical Use Cases

FreeToken is ideal for developers, researchers, and AI enthusiasts who want to:

• Run Large Models Locally: Deploy and experiment with massive LLMs (290B+ parameters) on personal hardware without relying on cloud infrastructure.
• Build Advanced AI Agents: Power sophisticated coding assistants, autonomous agents, and tool-use systems with local, high-performance LLM inference.
• Accelerate LLM Research: Facilitate rapid prototyping and experimentation with MoE architectures on readily available hardware.
• Develop Interactive AI Applications: Create responsive and engaging AI-powered applications that benefit from low-latency local inference.