--- title: "gateway vs Awesome-LLMOps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/missingstudio-gateway-vs-tensorchord-awesome-llmops" tools: ["missingstudio-gateway", "tensorchord-awesome-llmops"] --- # gateway vs Awesome-LLMOps *GraphCanon updated Aug 20, 2026* ## Verdict Pick gateway if aI Gateway offers a comprehensive infrastructure for deploying and managing production-grade AI apps with GRPC, protobuf, and support for large language models; 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. [gateway](https://www.missing.studio) reports 160 GitHub stars, 17 forks, and 10 open issues, last pushed Apr 8, 2024. [Awesome-LLMOps](https://github.com/tensorchord/Awesome-LLMOps) has 5.9k stars, 993 forks, and 247 open issues, last pushed May 21, 2026. Figures are from public GitHub metadata via [gateway's repository](https://github.com/missingstudio/gateway) and [Awesome-LLMOps's repository](https://github.com/tensorchord/Awesome-LLMOps). | | [gateway](/tools/missingstudio-gateway.md) | [Awesome-LLMOps](/tools/tensorchord-awesome-llmops.md) | | --- | --- | --- | | Tagline | Core infrastructure stack for building production-ready AI Applications | An awesome & curated list of best LLMOps tools for developers | | Stars | 160 | 5,915 | | Forks | 17 | 993 | | Open issues | 10 | 247 | | Language | Go | Shell | | Adopt for | AI Gateway offers a comprehensive infrastructure for deploying and managing production-grade AI apps with GRPC, protobuf, and support for large language models. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 | CC0-1.0 | | Categories | Inference & Serving, Model Training | Computer Vision, Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [gateway](/tools/missingstudio-gateway.md) | [Awesome-LLMOps](/tools/tensorchord-awesome-llmops.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 846d | 91d | | Open issues (now) | 10 | 247 | | Stars delta | Unknown | +28 (30d) | | Open issues delta | Unknown | +66 (30d) | | Full report | [trust report](/tools/missingstudio-gateway/trust.md) | [trust report](/tools/tensorchord-awesome-llmops/trust.md) | ## Decision facts: gateway - **Adopt for:** AI Gateway offers a comprehensive infrastructure for deploying and managing production-grade AI apps with GRPC, protobuf, and support for large language models. ## Decision facts: Awesome-LLMOps - **Adopt for:** 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. ## Choose when ### Choose gateway if… - gateway is primarily Go; Awesome-LLMOps is Shell. - License: gateway is Apache-2.0, Awesome-LLMOps is CC0-1.0. - Tags unique to gateway: ai-gateway, grpc, inference, production-ready. - gateway ships Docker support for self-hosted deployment. - Use when you need to deploy applications that require low-latency communication like gRPC services. ### Choose Awesome-LLMOps if… - Awesome-LLMOps is primarily Shell; gateway is Go. - License: Awesome-LLMOps is CC0-1.0, gateway is Apache-2.0. - Tags unique to Awesome-LLMOps: ai-development-tools, awesome-list, mlops. - Also covers Computer Vision, Data & Retrieval, Evaluation & Observability, LLM Frameworks, Speech & Audio. - - When you need a comprehensive directory of tools specifically focused on LLM development, training, fine-tuning, and management. ## When NOT to use gateway - Avoid if the project does not involve production-grade AI application deployment or specific needs of grpc and protobuf technologies. - Not suitable for teams preferring other programming languages over Go, as this tool is written entirely in Go. ## 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. ## Common questions ### What is the difference between gateway and Awesome-LLMOps? gateway: Core infrastructure stack for building production-ready AI Applications. 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 gateway over Awesome-LLMOps? Choose gateway over Awesome-LLMOps when gateway is primarily Go; Awesome-LLMOps is Shell; License: gateway is Apache-2.0, Awesome-LLMOps is CC0-1.0; Tags unique to gateway: ai-gateway, grpc, inference, production-ready; gateway ships Docker support for self-hosted deployment; Use when you need to deploy applications that require low-latency communication like gRPC services. ### When should I choose Awesome-LLMOps over gateway? Choose Awesome-LLMOps over gateway when Awesome-LLMOps is primarily Shell; gateway is Go; License: Awesome-LLMOps is CC0-1.0, gateway is Apache-2.0; Tags unique to Awesome-LLMOps: ai-development-tools, awesome-list, mlops; Also covers Computer Vision, Data & Retrieval, Evaluation & Observability, LLM Frameworks, Speech & Audio; - When you need a comprehensive directory of tools specifically focused on LLM development, training, fine-tuning, and management. ### When should I avoid gateway? Avoid if the project does not involve production-grade AI application deployment or specific needs of grpc and protobuf technologies. Not suitable for teams preferring other programming languages over Go, as this tool is written entirely in Go. ### 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 gateway or Awesome-LLMOps more popular on GitHub? Awesome-LLMOps has more GitHub stars (5,915 vs 160). Stars measure visibility, not whether either tool fits your constraints. ### Are gateway and Awesome-LLMOps open source? Yes - both are open-source projects on GitHub (gateway: Apache-2.0, Awesome-LLMOps: CC0-1.0). ### Where can I find alternatives to gateway or Awesome-LLMOps? GraphCanon lists graph-backed alternatives at [gateway alternatives](/tools/missingstudio-gateway/alternatives) and [Awesome-LLMOps alternatives](/tools/tensorchord-awesome-llmops/alternatives) ([gateway markdown twin](/tools/missingstudio-gateway/alternatives.md), [Awesome-LLMOps markdown twin](/tools/tensorchord-awesome-llmops/alternatives.md)), 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](/compare/missingstudio-gateway-vs-tensorchord-awesome-llmops.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, gateway or Awesome-LLMOps? gateway: Dormant. 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 gateway and Awesome-LLMOps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [gateway trust report](/tools/missingstudio-gateway/trust); [Awesome-LLMOps trust report](/tools/tensorchord-awesome-llmops/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=missingstudio-gateway`](/api/graphcanon/graph?tool=missingstudio-gateway) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_