I Tried 5 OpenRouter Alternatives So You Don't Have To

I set myself a rule for this one: no comparison table copied from someone else's blog post. If I was going to write about OpenRouter alternatives, I'd actually wire each one up to a real script and see what broke.

The project was small on purpose — a CLI tool that summarizes GitHub issues into a weekly digest, making maybe a few hundred model calls a week. Low enough stakes that I could afford to spend an evening swapping providers in and out without anything important depending on the outcome. Here's what actually happened with each one.

The baseline: what I was already running

My digest tool was already using OpenRouter with a plain fetch call — no SDK, just a base URL, an API key, and a model string. That's the part worth keeping in mind through this whole post: because most of these alternatives speak the same OpenAI-compatible /chat/completions shape, "trying" one mostly meant changing two environment variables, not rewriting the client.

// client.js — the one function every gateway below had to work with unmodified

async function chatCompletion(messages, model) {
  const response = await fetch(`${process.env.GATEWAY_BASE_URL}/chat/completions`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${process.env.GATEWAY_API_KEY}`,
    },
    body: JSON.stringify({ model, messages }),
  });

  if (!response.ok) {
    throw new Error(`Request failed: ${response.status} ${await response.text()}`);
  }

  return response.json();
}

module.exports = { chatCompletion };

Every gateway below got tested against this exact function. Anything that needed more than a .env change to work is called out explicitly, because that friction is itself useful information.

1. LiteLLM (self-hosted)

LiteLLM is the one genuinely different entry on this list, because it isn't a hosted service you point at — it's an open-source proxy you run yourself. I spun it up locally with the provided Docker image and pointed my client's GATEWAY_BASE_URL at http://localhost:4000. Setup took longer than every other option here, mostly because I had to configure provider API keys inside LiteLLM's own config file rather than just using one gateway key.

What that buys you: the request never leaves infrastructure you control, which matters if compliance or data residency is the actual reason you're looking at alternatives. What it costs you: you're now responsible for keeping a proxy running, patched, and monitored. For my low-stakes CLI tool this was overkill. For a team with an actual compliance requirement, it's close to the point of the whole exercise.

1. Together AI

Together AI is a direct inference provider rather than a multi-vendor router — it hosts open models itself rather than reselling access to other labs' APIs. The client code above worked against it without modification once I had a key, which was expected since it's OpenAI-compatible too. The catch, and it's not really a flaw, is that it's not a like-for-like OpenRouter replacement: you get the models Together AI actually runs, not a single key covering dozens of providers. If you've already settled on an open-weight model family and don't need multi-provider flexibility, this removes a routing hop entirely. If you still want to compare models across labs from one key, it's the wrong tool for that specific job.

1. Requesty

Requesty was the closest thing to a drop-in OpenRouter swap in terms of experience — same "one key, many models" pitch, same request shape, working against my unmodified client immediately. The meaningful difference I found reading through their docs while testing was the fee structure: a flat token-based markup rather than OpenRouter's credit-purchase-fee-plus-capped-BYOK model. Whether that's cheaper depends entirely on your usage pattern, which is exactly the kind of thing worth running your own numbers on rather than trusting either vendor's framing.

1. RouteAI

RouteAI also worked against the unmodified client on the first try — same OpenAI-compatible shape, key and base URL swap, nothing else to configure. It covers a different slice of the model landscape than some of the others here, with access to models like DeepSeek, Qwen, Kimi, GLM, and MiniMax, and bills per call with no monthly fee. For my digest tool specifically, which mostly needed a solid mid-tier model for summarization rather than a frontier reasoning model, this was one of the two gateways I actually left running after the evening was over — not because it's objectively "the best," but because it matched what this particular project needed without extra setup overhead.

1. Cloudflare AI Gateway

Cloudflare AI Gateway is a slightly different shape than the rest: it's designed to sit in front of your existing provider calls — including OpenRouter itself — adding caching, logging, and rate limiting rather than replacing the underlying model access entirely. I tested it by pointing my client at a Cloudflare-proxied endpoint in front of an existing OpenAI key. It's less "an OpenRouter alternative" in the strict sense and more "a layer you might put in front of any of these," which is worth knowing before you file it under the wrong category the way a couple of comparison lists do.

What I actually kept running

After the evening, my digest tool ended up split between two gateways: RouteAI for the routine weekly summarization calls, and my original OpenRouter setup left in place as a fallback for anything the primary model couldn't handle well. Nothing here was a dramatic verdict — the honest result of testing five alternatives to a small, low-volume tool is that several of them work fine, and the differences that matter (fee structure, self-hosting, model coverage) depend entirely on what you're actually building.

If I'd been building something with real compliance requirements, LiteLLM would have been the only serious option on this list. If I'd already committed to one open-weight model family, Together AI would have removed a layer I didn't need. For a small tool where "one key, reasonable pricing, no extra setup" was the whole requirement, RouteAI and Requesty were the two that just worked without me having to think about it further — which, for a project this size, was the actual bar.

The part worth repeating

None of this required a benchmark suite or a spreadsheet of features. Because the OpenAI-compatible shape is close to universal across this category, the real cost of testing an alternative is usually a .env file and twenty minutes, not a rewrite. If you're evaluating OpenRouter alternatives for your own project, that's the cheap experiment worth running before reading someone's ranked list — including this one.

TL;DR: I swapped five OpenAI-compatible gateways into an existing small project with minimal code changes — LiteLLM needed real self-hosting setup, Together AI is a direct provider rather than a router, and Requesty and RouteAI worked as near drop-in OpenRouter replacements, with RouteAI ending up as the one I kept running for routine calls.

Website: https://www.fastrouteai.com