AI Model Gateway

Share AI Model Gateway

Copy-ready links and short posts for introducing AI Model Gateway to operators evaluating self-hosted LLM routing, fallback, telemetry, config publishing, and rollback.

GitHub repository Try it quickly Copy post text Chinese share kit

Share with teams that operate internal LLM traffic. Ask for technical feedback first; star requests should stay conditional on fit.

Start links

Use these links when posting or replying.

Repository

Main project page, README, CI badge, source code, issues, release links, and star action.

Open GitHub repo

Fast trial

Packaged v1.4.4 archives, checksum verification, local config, runtime dirs, and supervised startup.

Open quick trial

Review evidence

Installability, CI gates, runtime smoke checks, feature proof, security boundaries, and release evidence.

Open review evidence

Preview card

Use a real product image in social posts.

The social preview card is a 1200x630 image backed by actual Admin UI screenshots. Use it for posts that need a visual instead of generic gateway copy.

Open social card
AI Model Gateway social preview card

Copy blocks

Keep posts short, factual, and feedback-oriented.

Short post

AI Model Gateway is a self-hosted LLM operations gateway in Go.

It focuses on local control: OpenAI/Anthropic-compatible entry points, provider routing and fallback, telemetry, benchmarks, config publish/rollback, diagnostics, and manifest-verified updates.

Repo: https://github.com/SSC-STUDIO/Ai-Model-Gateway
Fast trial: https://github.com/SSC-STUDIO/Ai-Model-Gateway#try-it-quickly

Feedback ask

I am looking for feedback from people running internal LLM gateways or proxy layers.

What provider failure modes matter most in production: 429s, timeouts, quota exhaustion, slow endpoints, config mistakes, or observability gaps?

Project: https://github.com/SSC-STUDIO/Ai-Model-Gateway
Review evidence: https://ssc-studio.github.io/Ai-Model-Gateway/#review-evidence

Audience fit

Post where the operational problem is relevant.

  1. Self-hosted teams. Local keys, local telemetry, and local rollout controls are the core fit.
  2. LLMOps users. Routing, fallback, benchmarks, diagnostics, and audit are the useful hooks.
  3. Go engineers. The compact supervised runtime is easier to inspect than a large platform stack.
  4. Gateway evaluators. Use comparison and review evidence links instead of broad claims.
Gateway comparison Self-hosted page Provider fallback page Chinese share kit Full promotion kit

Support discovery

Use the star request only after fit is clear.

If the project matches a self-hosted LLM operations workflow, a GitHub star helps other operators find it. If not, technical feedback is more useful than a star.

Star on GitHub Leave feedback