KTransformers
KTransformers is a flexible Python-centric framework for LLM inference optimization. It addresses the challenge of running and fine-tuning large language models on consumer-grade hardware by using CPU/GPU heterogeneous computing.
The framework enables low-VRAM full-precision inference of 100B+ parameter models on a single RTX 5090 with 32 GB VRAM. It supports full-parameter fine-tuning of such models on similar hardware without requiring multi-GPU clusters. No quantization is applied, preserving original model precision. A complete local deployment toolchain covers both inference and fine-tuning. It integrates with SGLang for GPU inference and supports multiple mainstream models including DeepSeek, Kimi, GLM, Qwen, and MiniMax.
KTransformers is built for developers seeking to run large models on accessible hardware without performance loss. It optimizes inference across CPU, GPU, and other accelerators. An active community shares benchmarks, configurations, and best practices. The project maintains documentation, a blog, and benchmark results, with downloads available and the source hosted on GitHub.
Open SourceApache-2.0CLIAPISelf-hosted
18.9kstars
1.5kforks
5features
2024since
Overview
5 featuresIn the AI & ML space, KTransformers takes a focused approach. It focuses on running and fine-tuning very large LLMs (100B+ parameters) on consumer-grade hardware with limited VRAM. KTransformers is an open-source project aimed at developers. KTransformers is open source under the Apache-2.0 license. It ships for the command line and API, and it can be self-hosted.
KTransformers builds and maintains KTransformers, and it first shipped in 2024. Development happens publicly on GitHub with 18.9k stars and 57 commits in the last 90 days. Key capabilities include Low-VRAM Inference, Full-Precision Inference, and Heterogeneous Computing. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
- Low-VRAM Inference
- Full-Precision Inference
- Heterogeneous Computing
- Full-Parameter Fine-Tuning
- Multi-Model Support
Tags
llm-inferenceheterogeneous-computelow-vramfull-precisionlocal-llm
AI capabilities
Text
Inference: LocalWeights: Open
Built with & integrations
Framework
Next.js
AI providers
local_oss
Connectors
API
Runs on
CLIAPI-onlySelf-hosted
Detected from
- Next.js
- x-nextjs-cache header · x-powered-by header · /_next/static/ in the HTML
- local_oss
- bllama in the HTML · bvllm in the HTML
Trust & compliance
License
Apache-2.0
Verified signals
Indexing history
1What PulseGate has recorded for this listing
- Indexed23 Jul · 09:06 UTCKTransformers – Flexible LLM Inference Framework verified against its public sourceSource: PulseGate · Open
Frequently asked questions about KTransformers
- What does KTransformers do?
- KTransformers focuses on running and fine-tuning very large LLMs (100B+ parameters) on consumer-grade hardware with limited VRAM. It is catalogued under AI & ML on PulseGate.
- Who should use KTransformers?
- KTransformers is an open-source project built for developers.
- Does KTransformers have a free plan?
- Yes — KTransformers is open source under the Apache-2.0 license and free to use.
- What platforms does KTransformers run on?
- KTransformers runs on the command line and API. It can also be self-hosted.
- Is KTransformers still active?
- The GitHub repository shows 57 commits in the last 90 days.
- What projects are similar to KTransformers?
- Similar projects tracked by PulseGate include Cliprise, chi-ai, and Ask AIs Anything.Cliprisechi-aiAsk AIs Anything
- Who develops KTransformers?
- KTransformers is developed by KTransformers.
- How long has KTransformers been around?
- KTransformers first shipped in 2024.
Also in AI & ML
Same category — not a similarity match