LMDeploy vs 
KTransformers
LMDeploy vs KTransformers compared for 2026 — features, license, ease of use, performance and which one to choose. Toolkit for compressing and serving LLMs vs Run huge MoE models on one consumer GPU.
Updated regularly · curated by OpenSourceAI.tech
LMDeploy vs KTransformers at a glance
| Spec | LMDeploy | KTransformers |
|---|---|---|
| Category | Inference server | Inference server |
| Type | Inference server | Inference optimizer |
| License | Apache-2.0 | Apache-2.0 |
| Runs locally | Self-hosted | Yes |
| Primary language | Python | Python |
| Ease of use | Advanced | Advanced |
| Best for | teams optimizing quantized serving | running huge MoE models on modest hardware |
| GitHub stars | 8k | 19.1k |
How LMDeploy and KTransformers score
| Criterion | LMDeploy | KTransformers |
|---|---|---|
| Popularity | 2.5 | 3.5 |
| Maintenance | 5.0 | 5.0 |
| Ease of use | 2.5 | 2.5 |
| Privacy | 4.5 | 5.0 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
LMDeploy
LMDeploy is a toolkit for compressing, quantizing and serving LLMs with high request throughput via its TurboMind engine.
- High throughput via the TurboMind engine
- Built-in quantization and compression
- Efficient KV-cache management
KTransformers
KTransformers uses clever CPU/GPU offloading to run very large mixture-of-experts models on a single consumer GPU that could not otherwise fit them.
- Runs 600B+ MoE models on one GPU
- Heterogeneous CPU/GPU offloading
- Drop-in OpenAI-compatible API
Key differences
LMDeploy is inference server, while KTransformers is inference optimizer. They also differ in how they run (Self-hosted vs Yes). In short, LMDeploy fits teams optimizing quantized serving, and KTransformers fits running huge MoE models on modest hardware.
Which should you choose?
Choose LMDeploy for teams optimizing quantized serving. Choose KTransformers for running huge MoE models on modest hardware.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is LMDeploy or KTransformers easier to use?
Both sit at a similar level (Advanced). Your choice should come down to fit rather than difficulty.
Are LMDeploy and KTransformers free?
LMDeploy is free and open source (Apache-2.0), and KTransformers is free and open source (Apache-2.0). Neither charges for the core software.
Can I run LMDeploy and KTransformers locally?
LMDeploy: self-hosted · KTransformers: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
LMDeploy vs KTransformers — which should I pick in 2026?
Choose LMDeploy for teams optimizing quantized serving. Choose KTransformers for running huge MoE models on modest hardware.
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