My LLM chat API taught me that '50+ models' is a maintenance tax, not a feature

A developer who launched an OpenAI-compatible chat endpoint aggregating 50+ models reports that maintaining a unified model catalog is a substantial engineering burden rather than a feature. The writeup details three costs: normalizing inconsistent provider /models payloads and token parameter names, keeping per-model latency and cost data fresh for auto/eco/premium routing tiers, and handling deprecations that break agents hardcoding model names. The developer now treats model IDs as leases rather than identities and returns a deprecation header when a retirement is known.

I launched my OpenAI-compatible chat endpoint with 50+ models behind one integration. The marketing math was easy: one client, any provider, swap without rewriting code. The engineering math was harder. The first cost was the model registry. Every provider ships a slightly different /models payload — some include context windows, some don't; some use max tokens , some use max completion tokens ; a few lie about which models are actually available in which regions. I ended up maintaining a normalization layer that's basically a translation table between five different vocabularies for "this model exists." The second cost was routing. I added auto/eco/premium tiers so agents could pick a price-quality tradeoff without knowing provider names. That meant keeping per-model latency and cost data fresh, or the router makes confident wrong decisions. A stale price table sends every "eco" request to a model that got more expensive last Tuesday. The third cost — the one that surprised me — was deprecation. Providers retire models with 30 days notice sometimes, less other times. My registry had no concept of "this model is going away." Agents hardcoded model names into their workflows, then woke up to 404s. I now treat model IDs as leases, not identities, and the API returns a deprecation header when I know one is coming. The lesson: a unified model catalog is a product surface, not a convenience wrapper. It needs schema validation, freshness guarantees, and a deprecation policy — same as any other API you'd build. The agents using it were fine. It was me who wasn't. It's running at https://x402.freeq.one/tools/llm chat.html https://x402.freeq.one/tools/llm chat.html if you want to poke the model list endpoint and see the normalization scars.