Comparison
archai vs Awesome-LLMOps
Verdict
Pick archai when archai is primarily Python; Awesome-LLMOps is Shell; pick Awesome-LLMOps when awesome-LLMOps is primarily Shell; archai is Python.
Markdown twin · archai alternatives · Awesome-LLMOps alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | archai | Awesome-LLMOps |
|---|---|---|
| Maintenance | Slowing (229d since push) As of today · github_public_v1 | Steady (51d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- archai
- Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
- Awesome-LLMOps
- An awesome & curated list of best LLMOps tools for developers
Stars
- archai
- 485
- Awesome-LLMOps
- 5.9k
Forks
- archai
- 93
- Awesome-LLMOps
- 901
Open issues
- archai
- 4
- Awesome-LLMOps
- 157
Language
- archai
- Python
- Awesome-LLMOps
- Shell
Adopt for
- archai
- -
- 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
- archai
- -
- Awesome-LLMOps
- -
Runtime
- archai
- -
- Awesome-LLMOps
- -
License
- archai
- MIT
- Awesome-LLMOps
- CC0-1.0
Last pushed
- archai
- Nov 24, 2025
- Awesome-LLMOps
- May 21, 2026
Categories
- archai
- Model Training
- Awesome-LLMOps
- Vector Databases, LLM Frameworks, Model Training
Trust and health
Maintenance
- archai
- Slowing (36%)
- Awesome-LLMOps
- Steady (60%)
Days since push
- archai
- 229d
- Awesome-LLMOps
- 51d
Open issues (now)
- archai
- 4
- Awesome-LLMOps
- 157
Full report
- archai
- Trust report
- Awesome-LLMOps
- Trust report
Choose archai if…
- archai is primarily Python; Awesome-LLMOps is Shell.
- License: archai is MIT, Awesome-LLMOps is CC0-1.0.
- Tags unique to archai: model-compression, automl, deep-learning, nas.
When NOT to use archai
- Last GitHub push was 230 days ago (slowing maintenance, Nov 24, 2025). Validate activity before betting a new project on archai.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Choose Awesome-LLMOps if…
- Awesome-LLMOps is primarily Shell; archai is Python.
- License: Awesome-LLMOps is CC0-1.0, archai is MIT.
- Tags unique to Awesome-LLMOps: llmops, shell, awesome-list, mlops.
- Also covers Vector Databases, LLM Frameworks.
- - 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 (microsoft/archai) · observed Jul 11, 2026
- GitHub forks (microsoft/archai) · observed Jul 11, 2026
- Last push (microsoft/archai) · observed Nov 24, 2025
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tensorchord/Awesome-LLMOps) · observed Jul 11, 2026
- GitHub forks (tensorchord/Awesome-LLMOps) · observed Jul 11, 2026
- Last push (tensorchord/Awesome-LLMOps) · observed May 21, 2026
- License file (CC0-1.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: archai 485 · Awesome-LLMOps 5.9k (synced Jul 11, 2026).
Common questions
- What is the difference between archai and Awesome-LLMOps?
- archai: Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.. 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 archai over Awesome-LLMOps?
- Choose archai over Awesome-LLMOps when archai is primarily Python; Awesome-LLMOps is Shell; License: archai is MIT, Awesome-LLMOps is CC0-1.0; Tags unique to archai: model-compression, automl, deep-learning, nas.
- When should I choose Awesome-LLMOps over archai?
- Choose Awesome-LLMOps over archai when Awesome-LLMOps is primarily Shell; archai is Python; License: Awesome-LLMOps is CC0-1.0, archai is MIT; Tags unique to Awesome-LLMOps: llmops, shell, awesome-list, mlops; Also covers Vector Databases, LLM Frameworks; - When you need a comprehensive directory of tools specifically focused on LLM development, training, fine-tuning, and management.
- When should I avoid archai?
- Last GitHub push was 230 days ago (slowing maintenance, Nov 24, 2025). Validate activity before betting a new project on archai. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- 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 archai or Awesome-LLMOps more popular on GitHub?
- Awesome-LLMOps has more GitHub stars (5,877 vs 485). Stars measure visibility, not whether either tool fits your constraints.
- Are archai and Awesome-LLMOps open source?
- Yes - both are open-source projects on GitHub (archai: MIT, Awesome-LLMOps: CC0-1.0).
- Where can I find alternatives to archai or Awesome-LLMOps?
- GraphCanon lists graph-backed alternatives at archai alternatives and Awesome-LLMOps alternatives (archai 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, archai or Awesome-LLMOps?
- archai: Slowing. Awesome-LLMOps: Steady. 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 archai and Awesome-LLMOps?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: archai trust report; Awesome-LLMOps trust report.