Awesome-LLMOps
An awesome & curated list of best LLMOps tools for developers
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
676views this month
Decision brief
Awesome-LLMOps is a curated list tailored for developers working with Large Language Models (LLMs), providing resources for model training, serving, evaluation, deployment, and more.
Good fit when
- - When you need a comprehensive directory of tools specifically focused on LLM development, training, fine-tuning, and management.
- - If your projects involve multiple stages of the LLMOps lifecycle and you require categorized resources to streamline different phases.
Avoid when
- - When you are looking for a hands-on platform or framework for developing and deploying models rather than just a resource list.
- - If your focus is on general artificial intelligence development that includes areas beyond LLMOps like image processing, robotics, or federated learning without the need for LLM-specific resources.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (121d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Backing
Company context for TensorChord. Display-only - separate from trust and ranking.
- Company
- TensorChord·GitHub org profile·Jul 11, 2026
- Commercial model
- Pure OSS·GitHub org profile (public repos)·Jul 11, 2026
Install
git clone https://github.com/tensorchord/Awesome-LLMOpsHow it fits your stack(31)
Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.
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Relationship graph
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Similar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A comprehensive curated list that covers a wide range of categories within the LLM and MLOps ecosystem, including frameworks, serving methods, security aspects, training processes, data handling, large scale deployment strategies, performance optimization techniques, AutoML solutions, optimizations in model management, federated learning approaches, and even specific models for various domains like CV, Audio, Robotics.
Capability facts
- Languages
- shell
Source: github.language · Sep 20, 2026
Categories
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README
Awesome LLMOps <a href="https://discord.gg/KqswhpVgdU" <img alt="discord invitation link" src="https://img.shields.io/discord/974584200327991326?style=flat&logo=discord&cacheSeconds=60" </a <a href="https://awesome.re" <img src="https://awesome.re/badge flat2.svg" </a An awesome...
For agents
This page has a .md twin and JSON over the API.