SSC-STUDIO / Ai-Model-Gateway

LLM Gateway Comparison

Choose an LLM gateway by operating model: broad provider proxy, observability platform, hosted broker, enterprise gateway stack, or self-hosted operations gateway with local config publishing and rollback.

Read full comparison View on GitHub Self-hosted gateway page

If this comparison helps your LLM gateway evaluation, star the repository after checking the project fit.

Decision frame

Most LLM gateways are good at different jobs.

The useful question is not which project wins universally. It is whether your team mainly needs provider breadth, observability, hosted access, gateway ecosystem integration, or a local operations workflow for routing changes and incidents.

Broad provider proxies

Projects such as LiteLLM and Portkey emphasize large provider catalogs, unified APIs, spend controls, and routing features.

Observability platforms

Tools such as Helicone are strongest when tracing, analytics, evaluations, and experiments are the primary missing piece.

Gateway stacks

Envoy AI Gateway, Kong, and adjacent stacks fit teams already standardized on gateway infrastructure and policy layers.

Self-hosted operations

AI Model Gateway focuses on local keys, OpenAI-compatible traffic, provider fallback, config publishing, telemetry, and rollback.

Comparison signal

Pick based on what must stay under local control.

AI Model Gateway is not trying to win on provider count. It is built for teams that want the LLM gateway to own operational workflows: preview, diff, publish, audit, rollback, provider probes, request logs, diagnostics, benchmark evidence, and update recovery.

Open the detailed comparison guide
AI Model Gateway monitoring workspace showing traffic, latency, and provider telemetry

Quick choices

Start with the tool category that matches your constraint.

Evaluate AI Model Gateway when

  • You want provider keys, routing policy, telemetry, and audit records to stay local.
  • OpenAI-compatible clients need one internal gateway URL.
  • Config changes need preview, diff, publish, audit, and rollback.
  • Provider health, diagnostics, request logs, benchmarks, and updates belong in one admin surface.

Start elsewhere when

  • Provider count is the top requirement.
  • A hosted model marketplace should own routing and billing.
  • The team already runs Kong, Envoy, or another gateway platform.
  • The only missing layer is observability on top of an existing proxy.

Evaluation links

Move from comparison to hands-on proof.

  1. Compare. Read the practical guide to decide which operating model fits your team.
  2. Self-host. Check whether local keys, telemetry, and rollback are hard requirements.
  3. Fallback. Run the provider fallback demo against fake OpenAI-compatible upstreams.
  4. Decide. Use the 15-minute path before spending deeper integration time.
Full comparison guide Self-hosted gateway page OpenAI-compatible gateway page Provider fallback gateway page 15-minute evaluation

Review evidence

Check installability, quality, and security before adopting it.

Release archive install

Try the packaged v1.4.4 runtime with checksum verification, local config, runtime directories, and supervised startup commands.

Open release install path

Quality evidence

Review CI gates, local reproduction commands, runtime smoke checks, feature proof points, and current capability boundaries.

Open quality evidence

Security and trust model

Inspect admin auth, same-origin browser writes, provider-key handling, SSRF defenses, telemetry sensitivity, and update trust.

Open security model

Next step

Validate the operating model, then decide whether it earns a star.

Start with the detailed comparison, then run the short evaluation path. If AI Model Gateway fits your self-hosted LLM operations needs, starring the repository helps other operators find it.

Star on GitHub Leave feedback