Comparison
oss-llmops-stack vs Awesome-LLMOps
Verdict
Pick oss-llmops-stack if the OSS LLMOps Stack is designed for managing and unifying LLM APIs with LiteLLM, and providing detailed observability through Langfuse; pick Awesome-LLMOps if 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.
Markdown twin · oss-llmops-stack alternatives · Awesome-LLMOps alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | oss-llmops-stack | Awesome-LLMOps |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3w · github_public_v1 | Slowing (91d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 4d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- oss-llmops-stack
- Modular open source LLMOps stack for LLM API unification, observability and prompt management
- Awesome-LLMOps
- An awesome & curated list of best LLMOps tools for developers
Stars
- oss-llmops-stack
- 142
- Awesome-LLMOps
- 5.9k
Forks
- oss-llmops-stack
- 7
- Awesome-LLMOps
- 993
Open issues
- oss-llmops-stack
- 1
- Awesome-LLMOps
- 247
Language
- oss-llmops-stack
- -
- Awesome-LLMOps
- Shell
Adopt for
- oss-llmops-stack
- The OSS LLMOps Stack is designed for managing and unifying LLM APIs with LiteLLM, and providing detailed observability through Langfuse.
- Awesome-LLMOps
- 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.
Persona
- oss-llmops-stack
- -
- Awesome-LLMOps
- -
Runtime
- oss-llmops-stack
- -
- Awesome-LLMOps
- -
License
- oss-llmops-stack
- MIT
- Awesome-LLMOps
- CC0-1.0
Last pushed
- oss-llmops-stack
- Jul 28, 2026
- Awesome-LLMOps
- May 21, 2026
Categories
- oss-llmops-stack
- Evaluation & Observability, Inference & Serving
- Awesome-LLMOps
- Computer Vision, Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training, Speech & Audio
Trust and health
Maintenance
- oss-llmops-stack
- Very active (96%)
- Awesome-LLMOps
- Slowing (36%)
Days since push
- oss-llmops-stack
- 0d
- Awesome-LLMOps
- 91d
Open issues (now)
- oss-llmops-stack
- 1
- Awesome-LLMOps
- 247
Stars delta
- oss-llmops-stack
- Unknown
- Awesome-LLMOps
- +28 (30d)
Open issues delta
- oss-llmops-stack
- Unknown
- Awesome-LLMOps
- +66 (30d)
Full report
- oss-llmops-stack
- Trust report
- Awesome-LLMOps
- Trust report
Choose oss-llmops-stack if…
- License: oss-llmops-stack is MIT, Awesome-LLMOps is CC0-1.0.
- Requirements: Ensure your environment supports both LiteLLM and Langfuse functionalities for seamless operation of the OSS LLMOps Stack.; Consider server capacity to handle the additional load introduced by using this stack for API unification and observability services..
- Tags unique to oss-llmops-stack: ai-gateway, llm-evaluation, open-source, prompt management.
- When you need to unify Multiple Large Language Model (LLM) APIs using LiteLLM's API mediation capabilities for efficient routing, cost control, and high-availability support.
When NOT to use oss-llmops-stack
- If your operational requirements are simple and you do not need comprehensive observability metrics or advanced LLM API unification capabilities provided by the stack.
- In scenarios where you prefer a proprietary software solution over an open-source tool for security, support, or compliance reasons.
Choose Awesome-LLMOps if…
- License: Awesome-LLMOps is CC0-1.0, oss-llmops-stack is MIT.
- Tags unique to Awesome-LLMOps: ai-development-tools, awesome-list, llmops, mlops.
- Also covers Computer Vision, Data & Retrieval, LLM Frameworks, Model Training, Speech & Audio.
- - When you need a comprehensive directory of tools specifically focused on LLM development, training, fine-tuning, and management.
When NOT to use Awesome-LLMOps
- - 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (langfuse/oss-llmops-stack) · observed Jul 29, 2026
- GitHub forks (langfuse/oss-llmops-stack) · observed Jul 29, 2026
- Last push (langfuse/oss-llmops-stack) · observed Jul 28, 2026
- License file (MIT) · observed Jul 29, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tensorchord/Awesome-LLMOps) · observed Aug 20, 2026
- GitHub forks (tensorchord/Awesome-LLMOps) · observed Aug 20, 2026
- Last push (tensorchord/Awesome-LLMOps) · observed May 21, 2026
- License file (CC0-1.0) · observed Aug 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: oss-llmops-stack 142 · Awesome-LLMOps 5.9k (synced Jul 29, 2026).
Common questions
- What is the difference between oss-llmops-stack and Awesome-LLMOps?
- oss-llmops-stack: Modular open source LLMOps stack for LLM API unification, observability and prompt management. Awesome-LLMOps: An awesome & curated list of best LLMOps tools for developers. See the comparison table for live GitHub stats and shared categories.
- When should I choose oss-llmops-stack over Awesome-LLMOps?
- Choose oss-llmops-stack over Awesome-LLMOps when License: oss-llmops-stack is MIT, Awesome-LLMOps is CC0-1.0; Requirements: Ensure your environment supports both LiteLLM and Langfuse functionalities for seamless operation of the OSS LLMOps Stack.; Consider server capacity to handle the additional load introduced by using this stack for API unification and observability services.; Tags unique to oss-llmops-stack: ai-gateway, llm-evaluation, open-source, prompt management; When you need to unify Multiple Large Language Model (LLM) APIs using LiteLLM's API mediation capabilities for efficient routing, cost control, and high-availability support.
- When should I choose Awesome-LLMOps over oss-llmops-stack?
- Choose Awesome-LLMOps over oss-llmops-stack when License: Awesome-LLMOps is CC0-1.0, oss-llmops-stack is MIT; Tags unique to Awesome-LLMOps: ai-development-tools, awesome-list, llmops, mlops; Also covers Computer Vision, Data & Retrieval, LLM Frameworks, Model Training, Speech & Audio; - When you need a comprehensive directory of tools specifically focused on LLM development, training, fine-tuning, and management.
- When should I avoid oss-llmops-stack?
- If your operational requirements are simple and you do not need comprehensive observability metrics or advanced LLM API unification capabilities provided by the stack. In scenarios where you prefer a proprietary software solution over an open-source tool for security, support, or compliance reasons.
- When should I avoid Awesome-LLMOps?
- - 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.
- Is oss-llmops-stack or Awesome-LLMOps more popular on GitHub?
- Awesome-LLMOps has more GitHub stars (5,915 vs 142). Stars measure visibility, not whether either tool fits your constraints.
- Are oss-llmops-stack and Awesome-LLMOps open source?
- Yes - both are open-source projects on GitHub (oss-llmops-stack: MIT, Awesome-LLMOps: CC0-1.0).
- Where can I find alternatives to oss-llmops-stack or Awesome-LLMOps?
- GraphCanon lists graph-backed alternatives at oss-llmops-stack alternatives and Awesome-LLMOps alternatives (oss-llmops-stack markdown twin, Awesome-LLMOps markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, oss-llmops-stack or Awesome-LLMOps?
- oss-llmops-stack: Very active. Awesome-LLMOps: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for oss-llmops-stack and Awesome-LLMOps?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: oss-llmops-stack trust report; Awesome-LLMOps trust report.