Live GitHub stats, community sentiment, and trend data for Openllm. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.
GitHub data synced: Mar 30, 2026 • Sentiment updated: Unknown
OpenLLM is different from alternatives because it allows developers to run any open-source LLMs as OpenAI-compatible APIs with a single command, making it easy to self-host and customize LLMs. The project takes a technical approach by providing a built-in chat UI, state-of-the-art inference backends, and a simplified workflow for cloud deployments. This solves the problem of having to manually set up and configure LLM servers, which can be time-consuming and require significant expertise.
Build a self-hosted LLM server for custom models — OpenLLM allows running any open-source LLMs as OpenAI-compatible APIs with a single command, Build a chat UI for interacting with LLMs — OpenLLM provides a built-in chat UI at the /chat endpoint for launched LLM servers, Build a cloud deployment for LLMs with Docker and Kubernetes — OpenLLM features a simplified workflow for creating enterprise-grade cloud deployments, Build a custom model repository for LLMs — OpenLLM supports adding custom model repositories to run custom models, Build an OpenAI-compatible API endpoint for LLMs — OpenLLM allows developers to run LLMs as OpenAI-compatible APIs with a single command
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
Official site: https://bentoml.com
Category: infrastructure
Tags: 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