RTP-LLM: Alibaba's high-performance LLM inference engine for diverse applications.
Star History
Momentum
+34
STARS · LAST 30 DAYS
1
PER DAY
#289
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +34 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +6 | +14 |
rtp-llm gained 34 stars in the last 30 days, about 1 a day, and now has 1.4K. It is about 3 years old and has averaged roughly 452 stars a year. It ranks #289 among Python repositories and #2,280 across all languages on GitHubRepo.
Trending Record
5
DAYS ON TRENDING
#1095
BEST RANK
Sep 24, 2026
FIRST APPEARANCE
Active
STATUS TODAY
rtp-llm has maintained a continuous presence across global trending indexes, peaking at #1095. Below is the 30-day activity profile:
💡 Overview
rtp-llm is an open-source project written in Python: RTP-LLM: Alibaba's high-performance LLM inference engine for diverse applications.
Engineered for speed, consistency, and developer ease, it solves common hurdles in gpt, inference, llama. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install rtp-llm⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
rtp-llm coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with rtp-llm.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install rtp-llm using your package manager: `pip install rtp-llm`
Initialize your project workspace or configuration file for rtp-llm.
Import rtp-llm into your codebase or invoke it directly from your terminal.
Execute your test suite or run `rtp-llm --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
alibaba/rtp-llm is currently ranked #2,280 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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Frequently Asked Questions
What does rtp-llm do? +
RTP-LLM: Alibaba's high-performance LLM inference engine for diverse applications.
What language is rtp-llm written in? +
The primary language is Python. Topics include: gpt, inference, llama, llm, llm-serving.
Is rtp-llm actively maintained? +
Yes, the last recorded push was on Sep 27, 2026 with 226 open issues being tracked.
How many stars does rtp-llm have? +
rtp-llm has 1,355 stars and 278 forks on GitHub.
How does rtp-llm rank among GitHub repositories? +
With 1,355 stars, alibaba/rtp-llm is ranked #2,280 globally across all repositories tracked on GitHubRepo and #289 among Python projects.
What license is rtp-llm distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
