llmflows vs vllm
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| llmflows | vllm | |
|---|---|---|
| Tagline | Simple, Explicit and Transparent LLM Applications | A high-throughput and memory-efficient inference and serving engine for LLMs |
| Stars | 706 | 86k |
| Forks | 35 | 19k |
| Open issues | 19 | 5.6k |
| Language | Python | Python |
| License | MIT | Apache-2.0 |
| Last pushed | Feb 20, 2025 | Jul 7, 2026 |
| Categories | Inference & Serving, Developer Tools | Inference & Serving, Model Training |
llmflows
LLMFlows is a framework in Python aimed at facilitating the creation of explicit and transparent AI applications powered by Large Language Models (LLMs). It supports building chatbots, Q&A systems, and similar applications without hidden prompts or calls.
Python
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