KTransformers
KTransformers: A self-hosted framework for efficient heterogeneous LLM inference, quantization, serving, and fine-tuning. Ranked #23 of 35 in AI Inference Engines by our editors (7.1/10); pricing: Free plan; best for CPU-GPU heterogeneous LLM inference.
At a glance
- Editor score7.1 / 10
- PricingFree plan
- Best forCPU-GPU heterogeneous LLM inference
- Free planYes
- Paid fromFree
- GPU accelerationYes
- Facts checked13 Oct 2026
Where it wins
- AMX/AVX CPU kernels with CUDA acceleration for NVIDIA GPUs
- INT4/INT8 backends, GGUF support, and MoE/NUMA-aware execution
- SGLang serving, LlamaFactory fine-tuning, Python API, and CLI
Where it doesn't
- CUDA acceleration is limited to NVIDIA GPU hardware
- Support channels are community and documentation
- Its integrations center on SGLang and LlamaFactory
Our verdict on KTransformers
KTransformers is an open-source framework for large-language-model inference and fine-tuning across heterogeneous CPU and GPU systems. It is aimed at teams and developers running models on self-hosted desktops or servers who need CPU inference, NVIDIA GPU acceleration, quantized execution, or a combination of those resources. The project offers Python and command-line interfaces and is available for Linux, Windows, and API-based use. Its Apache-2.0 license supports deployment across small, mid-market, and enterprise environments that can manage their own infrastructure.
The technical focus is broad within inference performance. KTransformers provides AMX- and AVX-optimized CPU kernels, CUDA acceleration for NVIDIA GPUs, and INT4/INT8 quantized inference backends. It also includes mixture-of-experts and NUMA-aware execution, plus GGUF and Llamafile CPU backend support. Model-format coverage includes FP8, BF16, FP16, INT4, INT8, GGUF, and GPTQ. For serving and model adaptation, the framework integrates with SGLang for production serving and LlamaFactory for fine-tuning, giving teams defined paths from local execution to those connected workflows.
KTransformers fits organizations that want open-source, self-hosted control over CPU-GPU inference and are comfortable selecting hardware, configuring runtimes, and maintaining deployments. The framework is less suited to buyers seeking a vendor-hosted service, a broad managed integration catalog, or support beyond community channels and documentation. NVIDIA-specific CUDA acceleration also makes hardware planning important, even though CPU execution is available. Choose it when heterogeneous compute, quantization, MoE execution, or GGUF workflows are central requirements; consider a different engine when managed operations or a wider platform ecosystem matters more than low-level deployment control.
Your product? Our editors can test KTransformers in depth and publish a review, labelled as paid · from $149/mo →
KTransformers pricing
KTransformers fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| GPU acceleration | Yes |
| CPU inference | Yes |
| Edge/mobile support | Not verified |
| Quantization support | Yes |
| Model formats | FP8, BF16, FP16, INT4, INT8, GGUF, GPTQ |
| Deployment targets | desktop, server, self-hosted |
| License | Apache-2.0 |
| Deployment | Self-hosted, Desktop |
| Platforms | Linux, Windows |
| Support | Community, Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 2 integrations: SGLang, LlamaFactory |
| Pricing | Free plan |
| Website | github.com |
| Facts checked | 13 Oct 2026 |
KTransformers integrations
KTransformers lists 2 integrations on its own site.
- SGLang
- LlamaFactory
Alternatives to KTransformers
- NVIDIA TensorRTA free SDK for compiling and running optimized deep-learning inference on NVIDIA GPUs.9.4
- vLLMA flexible open-source engine for teams serving LLMs across varied infrastructure.9.3
- Apache TVMA flexible open-source compiler for deploying models across CPUs, GPUs, mobile and edge hardware.9.2
See all KTransformers alternatives →
Used KTransformers? Be the first to review it
The editor score above is our own research. What this page doesn't have yet is a reader's view — what you used KTransformers for, what worked and what didn't. No stars are seeded and no review is paid for; an editor reads every one before it appears.
Write a reviewTwo minutes · verified accounts only · read by an editor before it appears
Featured on iTechGuides
KTransformers is listed in our AI Inference Engines directory. Add the badge to your site — it links back to this page.
<a href="https://www.itechguides.com/products/ktransformers/"><img src="https://www.itechguides.com/best/badge/ktransformers.svg" alt="Featured on iTechGuides" width="230" height="46"></a>
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.
Last updated · How we research and update