Comparison
Awesome-LLMOps vs gateway
Verdict
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; pick gateway if self-hosted firewall for securing AI applications with guardrails and content moderation.
Markdown twin · Awesome-LLMOps alternatives · gateway alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | Awesome-LLMOps | gateway |
|---|---|---|
| Maintenance | Steady (51d since push) As of 4d · github_public_v1 | Dormant (385d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 4d · osv@v1 | No lockfile (source not queried) As of today · 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
- Awesome-LLMOps
- An awesome & curated list of best LLMOps tools for developers
- gateway
- Self-hosted firewall for securing AI applications with guardrails and content moderation.
Stars
- Awesome-LLMOps
- 5.9k
- gateway
- 126
Forks
- Awesome-LLMOps
- 901
- gateway
- 12
Open issues
- Awesome-LLMOps
- 157
- gateway
- 0
Language
- Awesome-LLMOps
- Shell
- gateway
- Python
Adopt for
- 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.
- gateway
- Self-hosted firewall for securing AI applications with guardrails and content moderation.
Persona
- Awesome-LLMOps
- -
- gateway
- -
Runtime
- Awesome-LLMOps
- -
- gateway
- -
License
- Awesome-LLMOps
- CC0-1.0
- gateway
- Other
Last pushed
- Awesome-LLMOps
- May 21, 2026
- gateway
- Jun 25, 2025
Categories
- Awesome-LLMOps
- Computer Vision, Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training, Speech & Audio
- gateway
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- Awesome-LLMOps
- Steady (60%)
- gateway
- Dormant (18%)
Days since push
- Awesome-LLMOps
- 51d
- gateway
- 385d
Open issues (now)
- Awesome-LLMOps
- 157
- gateway
- 0
Full report
- Awesome-LLMOps
- Trust report
- gateway
- Trust report
Choose Awesome-LLMOps if…
- Awesome-LLMOps is primarily Shell; gateway is Python.
- License: Awesome-LLMOps is CC0-1.0, gateway is Other.
- Tags unique to Awesome-LLMOps: ai-development-tools, awesome-list, llmops, mlops.
- Also covers Computer Vision, Data & Retrieval, Inference & Serving, 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.
Choose gateway if…
- gateway is primarily Python; Awesome-LLMOps is Shell.
- License: gateway is Other, Awesome-LLMOps is CC0-1.0.
- Pricing: Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment.
- Requirements: Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time.
- Tags unique to gateway: content-moderation, docker-compose, guardrails, pii-redaction.
- gateway ships Docker support for self-hosted deployment.
- When you need to self-host a secure gateway for LLM-based AI applications that requires local deployment via Docker
When NOT to use gateway
- Avoid if you are looking for cloud-managed services, as this tool is designed solely for local or self-hosted environments
- Not suitable if you require extensive customization beyond the provided policies.yaml file and predefined guardrails for content moderation and security
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (trylonai/gateway) · observed Jul 15, 2026
- GitHub forks (trylonai/gateway) · observed Jul 15, 2026
- Last push (trylonai/gateway) · observed Jun 25, 2025
- License file (Other) · observed Jul 15, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: Awesome-LLMOps 5.9k · gateway 126 (synced Jul 11, 2026).
Common questions
- What is the difference between Awesome-LLMOps and gateway?
- Awesome-LLMOps: An awesome & curated list of best LLMOps tools for developers. gateway: Self-hosted firewall for securing AI applications with guardrails and content moderation.. See the comparison table for live GitHub stats and shared categories.
- When should I choose Awesome-LLMOps over gateway?
- Choose Awesome-LLMOps over gateway when Awesome-LLMOps is primarily Shell; gateway is Python; License: Awesome-LLMOps is CC0-1.0, gateway is Other; Tags unique to Awesome-LLMOps: ai-development-tools, awesome-list, llmops, mlops; Also covers Computer Vision, Data & Retrieval, Inference & Serving, 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 choose gateway over Awesome-LLMOps?
- Choose gateway over Awesome-LLMOps when gateway is primarily Python; Awesome-LLMOps is Shell; License: gateway is Other, Awesome-LLMOps is CC0-1.0; Pricing: Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment; Requirements: Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time; Tags unique to gateway: content-moderation, docker-compose, guardrails, pii-redaction; gateway ships Docker support for self-hosted deployment; When you need to self-host a secure gateway for LLM-based AI applications that requires local deployment via Docker.
- 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.
- When should I avoid gateway?
- Avoid if you are looking for cloud-managed services, as this tool is designed solely for local or self-hosted environments Not suitable if you require extensive customization beyond the provided policies.yaml file and predefined guardrails for content moderation and security
- Is Awesome-LLMOps or gateway more popular on GitHub?
- Awesome-LLMOps has more GitHub stars (5,877 vs 126). Stars measure visibility, not whether either tool fits your constraints.
- Are Awesome-LLMOps and gateway open source?
- Yes - both are open-source projects on GitHub (Awesome-LLMOps: CC0-1.0, gateway: Other).
- Where can I find alternatives to Awesome-LLMOps or gateway?
- GraphCanon lists graph-backed alternatives at Awesome-LLMOps alternatives and gateway alternatives (Awesome-LLMOps markdown twin, gateway 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, Awesome-LLMOps or gateway?
- Awesome-LLMOps: Steady. gateway: Dormant. 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 Awesome-LLMOps and gateway?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-LLMOps trust report; gateway trust report.