OpenLLM open source analysis

Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.

Project overview

⭐ 12028 · Python · Last activity on GitHub: 2025-12-22

GitHub: https://github.com/bentoml/OpenLLM

Why it matters for engineering teams

OpenLLM addresses the challenge of deploying and managing open-source large language models (LLMs) with ease and consistency. It provides a production ready solution that enables software engineers, particularly those in machine learning and AI engineering roles, to run models like Llama and Vicuna as OpenAI-compatible API endpoints. This simplifies integration into existing systems and supports fine-tuning workflows, making it a practical choice for teams focused on model inference and MLOps. The project is mature enough for production use, offering reliability and scalability in cloud environments. However, it may not be the right choice for teams seeking highly custom or experimental model architectures, or those who prefer fully managed, proprietary LLM services without self hosting responsibilities.

When to use this project

OpenLLM is a strong choice when teams need a self hosted option for running open-source LLMs with standardised APIs and want control over their inference infrastructure. Teams should consider alternatives if they require minimal setup or prefer vendor-managed solutions with less operational overhead.

Team fit and typical use cases

Machine learning engineers and AI engineering teams benefit most from OpenLLM as an open source tool for engineering teams aiming to deploy and fine-tune LLMs in production. They typically use it to serve models for natural language processing tasks within products such as chatbots, recommendation engines, and content generation platforms. The project fits well in environments where control over model hosting and inference pipelines is essential.

Best suited for

Topics and ecosystem

bentoml fine-tuning llama llama2 llama3-1 llama3-2 llama3-2-vision llm llm-inference llm-ops llm-serving llmops mistral mlops model-inference open-source-llm openllm vicuna

Activity and freshness

Latest commit on GitHub: 2025-12-22. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.