rtp-llm vs vllm
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| rtp-llm | vllm | |
|---|---|---|
| Tagline | RTP-LLM: Alibaba's high-performance LLM inference engine | A high-throughput and memory-efficient inference and serving engine for LLMs |
| Stars | 1.3k | 86k |
| Forks | 227 | 19k |
| Open issues | 163 | 5.6k |
| Language | Cuda | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last pushed | Jul 7, 2026 | Jul 7, 2026 |
| Categories | Inference & Serving | Model Training, Inference & Serving |
rtp-llm
RTP-LLM is a Large Language Model (LLM) inference acceleration engine developed by Alibaba to support diverse applications with enhanced performance and flexibility through CUDA-based optimizations, including quantization techniques and dynamic batching. It supports deployment across various hardware platforms.
Cuda
vllm
vLLM is a fast and efficient library designed to serve large language models (LLMs) with high throughput while being mindful of computational resources. It supports various model optimizations, quantization techniques, and offers seamless integration with popular Hugging Face models.
Python