LLM gateway — one API for every model: routing, fallback, billing & observability (2026)

An LLM gateway is a single API endpoint that sits in front of many large-language-model providers. Instead of integrating Anthropic, Google and OpenAI separately — three SDKs, three keys, three invoices — your app sends one request shape to one base URL with one key, and the gateway routes it, retries on failure, meters usage and enforces spend limits. It is the control plane between your product and the models.

What an LLM gateway does

A production LLM gateway carries six responsibilities. The first is what makes the other five possible: a single, stable API surface.

One endpoint, every provider

The gateway turns “add a provider” into a one-string change. The same client reaches Claude, Gemini and GPT — you route by setting the model field:

from openai import OpenAI

# One LLM gateway endpoint + one key fronts every provider.
gateway = OpenAI(
    api_key="sk-kn-...",
    base_url="https://api.kunavo.com/v1",  # the LLM gateway
)

# Route by changing a string — no per-provider SDK, key or client.
def ask(model: str, prompt: str) -> str:
    r = gateway.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": prompt}],
    )
    return r.choices[0].message.content

print(ask("claude-sonnet-4-6", "Draft a release note."))   # Anthropic
print(ask("gemini-2-5-flash", "Classify this ticket."))    # Google
print(ask("gpt-5-4", "Summarize the thread."))             # OpenAI

LLM gateway vs API gateway

A traditional API gateway — Kong, AWS API Gateway, NGINX — routes generic HTTP and handles auth, quotas and rate limiting. An LLM gateway is purpose-built for model traffic: it understands tokens and streaming, does prompt caching and model routing, meters spend per key, and (for inference gateways) bills usage. They compose — some teams put an LLM gateway behind their existing API gateway. For the conceptual deep dive, see what is an AI gateway?, and Kunavo vs Kong AI Gateway for the enterprise API-management case.

Two kinds of LLM gateway

The category splits by who holds the provider relationship:

BYO-key gateways layer control and observability on top of your existing Anthropic, Google and OpenAI accounts — you still hold those keys. Inference gateways front the providers themselves: top up one balance, never touch a provider console. See Kunavo vs Portkey, Helicone, LiteLLM and OpenRouter for the full side-by-sides.

Security & compliance

A gateway is also the natural place to enforce security: keys never leave your server, per-key spend caps and rate limits contain blast radius, and centralized logging gives you one audit trail. For regulated deployments, Kunavo offers a DPA and Zero Data Retention routing through the providers' enterprise tiers — the region-by-region playbook is in the AI compliance guide.

Kunavo as an LLM gateway

Kunavo is an inference LLM gateway. It is OpenAI-wire-compatible at https://api.kunavo.com/v1, so if your code can call the OpenAI API it can call Kunavo by changing only the base URL. One sk-kn- bearer token reaches Claude, Gemini, GPT and the rest of the catalog — priced roughly 60% under the providers' list rates, pay-as-you-go from a $10 top-up, one Stripe-billed wallet. Unlike a text-only router it also fronts image, video and audio generation on the same key.

Start with the quickstart, see the OpenAI-compatible API guide for how the wire format lets you move between local (Ollama) and hosted models without a code change, and the LLM cost calculator to estimate what a workload will cost — or the rest of the free cost tools, which price the Claude and OpenAI sides under their own caching rules. If you switch a coding client between providers rather than committing to one, the CC Switch setup covers that from the gateway side.

FAQ