LMDeploy
High-throughput and low-latency inference framework for LLMs and VLs
Pricing
Free tier
Flat rate
Adoption
↗RisingLicense
Open Source
Data freshness
Verified · Jul 16, 2026Overview
What is LMDeploy?
LMDeploy is a high-performance inference and serving framework designed to deliver fast and efficient deployment of large language models (LLMs) and vision-language models (VLs). It focuses on minimizing latency while maximizing throughput, making it ideal for real-time applications.
Key differentiator
“LMDeploy stands out with its focus on high-throughput and low-latency inference, making it ideal for real-time applications that require efficient deployment of large language models and vision-language models.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development in C++, secondary support for Python; other languages require community effort
High-performance tuning requires deep understanding of underlying architecture and configurations
Fit analysis
Who is it for?
✓ Best for
Teams needing high-throughput and low-latency inference for LLMs and VL models in production environments
Projects requiring self-hosted deployment options with optimized performance
Applications that demand real-time responses from large language or vision-language models
✕ Not a fit for
Developers looking for cloud-based managed services without the need to manage infrastructure
Teams preferring a more user-friendly web interface over command-line tools and libraries
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with LMDeploy
Step-by-step setup guide with code examples and common gotchas.