Three GPU affiliate programs I wired into an AI tool directory

When I decided to drop AdSense and bet on affiliate monetization for my AI tools directory, Amazon was the obvious first integration — books and GPU hardware are contextually reasonable on a site full of open-source AI models. But Amazon's conversion story for developer-adjacent products is weak. The users landing on a LLaMA or Whisper model page are not there to buy a deep learning textbook; they're evaluating whether to self-host something.

That realization pointed toward GPU cloud affiliates. People who read model pages are more likely to spin up a pod than click a book link. Here's what I integrated, how, and what I'm watching.

The Three Programs

Program	Commission structure	Referral mechanism
RunPod	% of referred user's spending	Referral code in URL
Vast.ai	% of referred user's spending	Referral code in URL
Hetzner Cloud	One-time credit on signup	Custom referral link

All three use simple referral codes embedded in URLs — no SDK, no iframe, just a URL parameter. That's intentional; I didn't want JavaScript dependencies on a statically generated site.

How the Integration Works

The monetization package exports three URL builder functions:

// packages/shared/src/monetization/index.ts

export function runpodReferralUrl(ref: string | null): string | null {
  if (!ref) return null;
  return `https://www.runpod.io/?ref=${encodeURIComponent(ref)}`;
}

export function vastReferralUrl(ref: string | null): string | null {
  if (!ref) return null;
  return `https://cloud.vast.ai/?ref_id=${encodeURIComponent(ref)}`;
}

export function hetznerReferralUrl(ref: string | null): string | null {
  if (!ref) return null;
  return `https://hetzner.cloud/?ref=${encodeURIComponent(ref)}`;
}

Each function returns null when the environment variable isn't set — so links simply don't render in development or in preview deployments where I haven't configured the ref codes. No dead links, no placeholder text.

On the model detail page, I build the affiliate sidebar conditionally based on pipeline_tag:

const aff = getAffiliateConfig();

// Only show GPU affiliates for model types where self-hosting is plausible
const showGpuLinks = isLLM || isVision;

const gpuLinks = showGpuLinks ? [
  { label: "RunPod", note: "On-demand GPU pods", url: runpodReferralUrl(aff.runpodRef) },
  { label: "Vast.ai", note: "Marketplace GPUs", url: vastReferralUrl(aff.vastRef) },
].filter((p): p is { label: string; note: string; url: string } => p.url !== null) : [];

Embedding models, classification models, and anything with a null pipeline_tag don't get the GPU sidebar. The reasoning: someone using a 384-dim sentence transformer doesn't need a GPU pod — they're calling an API or running inference on CPU. Showing GPU rental links there would be noise.

What I'm Watching

I won't fabricate numbers at week four. What I can say:

RunPod is easier to link to than Vast.ai. RunPod's referral URL resolves cleanly with no login wall before the landing page. Vast.ai drops you directly on the instance marketplace, which is great if you already know what you're doing and confusing if you don't. For a cold click from a model page, RunPod's onboarding is softer.

Hetzner is the odd one out. Hetzner Cloud is a German VPS provider — good for CPU-heavy workloads, affordable storage, strong EU datacenter story. It's on the model pages for users who want to run lighter inference (embedding models on CPU, small classifiers) at a lower cost than GPU cloud. The problem: the conversion path is long. A user has to sign up, set up a server, install dependencies, and deploy a model before Hetzner earns anything. I added it anyway because the referral credit structure means even a few conversions matter, but I'm skeptical it'll generate meaningful revenue without editorial content guiding the setup.

Amazon still outranks all of them in raw click volume — because the Amazon links are on more pages (all model pages, not just LLM/vision) and Amazon's brand is more trusted for an impulse click. Whether clicks convert is a different question I can't answer yet.

What I'd Add Next

DigitalOcean and Vultr are already in the affiliate config object but not yet wired to any page. DigitalOcean's GPU droplets are new-ish and not as well-known as RunPod; Vultr has a straightforward referral program. I'll add both once I have any signal about whether the current GPU links are being used.

Contextual text around the affiliate links. Right now the sidebar is just label + note + arrow. A one-sentence "why you'd use this" blurb next to each link would reduce the blank-stare click gap — especially for Vast.ai, where first-time users don't immediately understand the marketplace model.

Separate referral codes per site. I'm running the same referral codes across all three directories right now, which means I can't attribute a conversion to the AI tools directory vs a future expansion. When the programs reach any meaningful click volume, I'll register site-specific codes.

The actual implementation is simple — three URL builder functions, one conditional block in the page component, and a handful of env variables. The hard part isn't the code; it's choosing contextually relevant programs and placing them on pages where a user actually has purchase intent.

Part of an ongoing 6-month experiment running three AI-curated directory sites. The technical claims here are real; this article was AI-assisted.