I Ran My Project Through OpenRouter Instead of Picking One AI API – Here's the Real Trade-offToolsAI

OpenAI banned my account twice. Not for anything I could point to. No warning, no explanation, no appeal that went anywhere. Just gone, with whatever was running on it.

The first time, I shrugged it off. The second time, I realized the problem wasn't OpenAI. The problem was that I'd built two production bots, Summary and Lidar, on a foundation I didn't control and couldn't predict.

Summary reads a list of Telegram channels and turns them into a daily digest. Lidar scans business community chats for messages that look like service requests and forwards them to the right person. Neither is complicated. Both depend entirely on an LLM being available when a cron job fires. When the API access disappears, the bots don't fail gracefully. They just stop.

That's the part that actually changed how I build. Not the ban itself, the fact that I had no fallback. One company's moderation decision, right or wrong, could take down something people relied on daily.

The fix wasn't a better provider. It was not depending on one.

I moved both bots onto OpenRouter, a single API that routes requests across hundreds of models from different providers. The pitch is simple: one endpoint, one bill, swap models without rewriting integration code. The reality took some tuning to get right.

Here's the actual config, not the hand-wavy version.

OpenRouter's request body takes a provider object on top of the normal model and messages fields. Two parameters do almost all the work: order, your priority list of providers, and allow_fallbacks, which decides whether OpenRouter can leave that list if everyone on it fails.

LIDAR

(lead detection across 80+ chats) runs hundreds of classification calls a day.

It's a yes/no filter, not a reasoning task, so I route it at a cheap, fast model first and let it fall through if that provider is struggling:

{ "model": "openai/gpt-4o-mini", "messages": [...], "provider": { "order": ["openai", "groq"], "allow_fallbacks": true, "sort": "price" } }

sort: "price" turns off OpenRouter's default load balancing and just walks my order list top to bottom. If the first provider 5xx's or rate-limits me, OpenRouter retries with the next one automatically, same request, no code on my end to catch the failure and retry manually.

SUMMARY

Summary runs once a day, so cost stops mattering and output quality becomes the entire product. Here I don't want load balancing picking the cheapest option, I want a specific model, with a named fallback if that exact provider is down:

{ "model": "anthropic/claude-sonnet-4-6", "messages": [...], "provider": { "order": ["anthropic"], "allow_fallbacks": false }, "models": ["anthropic/claude-sonnet-4-6", "openai/gpt-5"] }

allow_fallbacks: false on the provider object stops OpenRouter from quietly swapping providers for that model. The top-level models array is the real safety net here, an ordered list of model IDs OpenRouter tries in sequence if the first one errors out entirely. Two different fallback mechanisms doing two different jobs: provider-level for "Anthropic is briefly down," model-level for "something has gone seriously wrong and I need a different model to pick up the slack."

That order array is the entire fix for what happened to me.

Before, my bots had model: "gpt-4o-mini" and nothing else, an implicit, undocumented dependency on one company staying happy with my account. Now a ban or outage on any single provider in that list isn't a 3am page, it's a line in a log file. The request just lands on whoever's next.

It's not free of friction. Free-tier models on OpenRouter exist mostly so providers can collect training data from your prompts, which means production traffic shouldn't touch them. I also hit a wall with video generation, specifically Seedance 2.0, where I could trigger a job but never got the finished output back, not through the interface, not through the API. Newer generative-media models on these aggregator platforms are still rough; text completion is solid, video is not there yet.

What I actually changed isn't "use OpenRouter." It's the assumption underneath it: any single AI provider is a dependency that can disappear without notice, and infrastructure that depends on a daily cron job should never have a single point of failure that's outside your control. The ban was the wake-up call. The architecture is the actual fix.

If you're running anything in production on a single model provider right now, ask yourself what happens the day they ban you for no reason. If the honest answer is "everything stops," that's worth fixing before it happens, not after.