rohit.vision

KTransformers

WIP nlp-llms heterogeneous-computing inference ktransformers kvcache llm nlp serving 1 min read

Flexible framework for running massive LLMs locally via CPU/GPU heterogeneous computing

Overview

KTransformers (by KVCache AI / Approaching.AI) is a flexible framework designed to run massive large language models (like DeepSeek-V3 or massive MoEs) on modest local hardware.

It acts as a research toolkit that lowers the barrier to local deployment by leveraging CPU-GPU heterogeneous computing.

Key Concepts

  • Hardware Offloading: It intelligently offloads certain layers (e.g., MoE expert layers) to the CPU while keeping critical computation on the GPU. This allows you to run models that dramatically exceed your VRAM limits without needing a massive fleet of high-end GPUs.
  • Transformers-Compatible Interface: By injecting optimized modules with just a single line of code, you get access to a standard Transformers-compatible pipeline.
  • API Support: It provides RESTful APIs compliant with both OpenAI and Ollama formats, plus a built-in ChatGPT-like Web UI.

TODO: Add notes on configuring the CPU/GPU split and optimizing memory bandwidth.