Open Source LLM API Gateway Alternatives Compared

If you're searching for "open source LLM API gateway alternatives," you're probably trying to solve one of two problems: you want a self-hosted layer that unifies multiple LLM providers behind one API, or you're evaluating whether to run that infrastructure yourself versus paying for a managed service. This article covers both — the main open source gateways worth knowing, what they actually do well, and where they fall short compared to a hosted option.

An LLM API gateway sits between your application and one or more model providers (Anthropic, OpenAI, local models, etc.). It typically handles routing, retries, rate limiting, logging, and sometimes caching or cost tracking. The open source projects in this space range from thin proxy libraries to full platforms with dashboards. None of them are drop-in identical — picking the right one depends on how much operational work you're willing to take on.

What an LLM API gateway actually does

Before comparing tools, it's worth being precise about the job:

• Routing — sending requests to the right model/provider, sometimes with fallback logic
• Normalization — exposing a consistent request/response shape across providers
• Observability — logging prompts, tokens, latency, and errors
• Access control — issuing scoped API keys instead of sharing one root provider key
• Rate limiting and quotas — protecting your provider account from runaway usage

Most open source gateways cover routing and normalization well. Access control, team management, and billing-grade usage metadata are usually thinner — that's the gap managed platforms tend to fill.

Popular open source LLM API gateway options

LiteLLM

LiteLLM is probably the most widely adopted option. It's a Python proxy (and SDK) that exposes an OpenAI-compatible API in front of 100+ providers, including Anthropic. You run it as a server, point your app at it, and it handles translation between formats. It supports fallback chains, budgets, and a basic admin UI.

Tradeoff: you're running a Python service, managing its config (YAML or a database), and handling its scaling, upgrades, and security patches yourself.

Portkey Gateway (open source core)

Portkey's gateway component is open source and focuses on reliability features — retries, fallbacks, caching, and load balancing across providers. The hosted Portkey product adds observability and analytics on top, but the gateway itself can run standalone.

Tradeoff: the open source core is intentionally narrow; richer features live behind the paid product, which is a common pattern in this space.

BricksLLM

A lighter-weight Go-based proxy focused on key management and spend limits in front of OpenAI/Anthropic-style APIs. Useful if you specifically want per-key budget enforcement without adopting a full platform.

Helicone

Technically an observability layer more than a router, but often used as a lightweight proxy since you point traffic through it to get logging and cost tracking. Self-hostable, with a hosted version available too.

Kong AI Gateway / TensorZero

Kong's AI Gateway plugin extends an existing API gateway (Kong) with LLM-specific routing and semantic caching — a good fit if you already run Kong. TensorZero is newer, aimed more at structured observability and experimentation (A/B testing prompts/models) than simple proxying.

The real tradeoff: self-hosting vs managed

Every option above gives you source code and infrastructure control, but that control comes with ongoing cost:

• You provision and patch the server(s)
• You handle TLS, scaling, and uptime
• You build or configure dashboards for usage and billing visibility
• You still need a provider account and API key behind the gateway — the gateway doesn't replace your Anthropic relationship, it sits in front of it

For a solo developer prototyping, running LiteLLM locally for an afternoon is fine. For a team shipping a product with multiple engineers calling Claude, the operational surface area grows fast: who rotates keys, who sees per-feature cost, who gets paged if the proxy goes down.

# Self-hosted gateway example (generic, provider-agnostic)
curl https://your-litellm-host.internal/v1/chat/completions \
  -H "Authorization: Bearer $GATEWAY_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "claude-3-5-sonnet", "messages": [{"role": "user", "content": "Hello"}]}'

That request works, but someone on your team now owns your-litellm-host.internal.

Where a managed layer like SubToAPI fits

If what you actually need is a clean HTTPS API in front of your existing Claude access — scoped application keys, streaming, tool use, and per-key usage metadata — without standing up and maintaining a gateway yourself, SubToAPI is built for exactly that gap. It gives you sub_live_... application keys instead of sharing a root key, a dashboard for usage across a team, and seat-based plans instead of infrastructure to babysit.

const res = await fetch("https://api.subtoapi.app/v1/messages", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.SUBTOAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "claude-3-5-sonnet",
    messages: [{ role: "user", content: "Summarize this ticket." }],
  }),
});

It's not a multi-provider router like LiteLLM — it's focused specifically on making Claude access production-ready for teams: streaming (see /docs/streaming), tool use (see /docs/tools), and usage visibility, all without you running a server. Start with /docs/quickstart, or check /pricing if you want Solo, Team, or Scale seats.

Choosing between the two

Pick an open source gateway if:

• You need to route across many different model providers, not just Claude
• You have the engineering capacity to run and secure another service
• You want full control over caching and routing logic

Pick a managed API layer if:

• Your primary need is Claude access with proper key scoping and team usage data
• You'd rather not operate infrastructure for this
• You want to be live in minutes rather than after a deployment cycle

questions

Are open source LLM gateways free to run in production? The software is free, but hosting, scaling, monitoring, and securing the service is not — budget for the same operational overhead as any other internal API you run.

Can I use an open source gateway and a managed API together? Yes. Some teams route non-Claude traffic through an open source gateway like LiteLLM while using a dedicated Claude layer like SubToAPI for application keys, streaming, and usage tracking on Claude specifically.

Do these gateways replace my Anthropic account? No. Every gateway, open source or managed, still sits in front of your underlying provider credentials — they manage access and routing, not the model relationship itself.