Free LLM Tiers Are Lying to You — Model Rotation Saved My Agent

A developer built a GitHub issue triage agent on free LLM tiers and found that free endpoints frequently return 503 errors, causing most calls to fail. The solution was to implement model rotation with instant failover across multiple free models, which dramatically improved reliability. The developer shared the full project in a public repository, emphasizing that failover is the first engineering task when building on free tiers.

I built a small autonomous agent GitHub issue triage that runs entirely on free LLM tiers — no API budget, no GPU, no AWS account. The project itself is ~250 lines and works. The interesting part is what the free tier did to me. The plan was simple: every open issue → LLM → JSON verdict. First real run on a big repo: almost every call failed . Not because the prompt was bad — because the model endpoint answered with 503 Service Unavailable . Free endpoints on popular models are chronically overloaded; they accept the request and then just… don't. This isn't hypothetical. My scan of facebook/react 22 items hit 503s repeatedly; the "free" model that the docs told me to use was effectively down half the time. The agent now holds an ordered list of models and tries them one by one until one answers: js const MODELS = 'liquid/lfm-2.5-2.6b:free', // fast, usually up 'thinkingmachines/inkling-small:free', // backup 'nvidia/nemotron-3.5-lightning:free', 'cohere/north-mini-code:free', for const model of MODELS { try { return await call model, prompt } catch {} } Semantics matter: any non-2xx or empty response is treated as a failure and we move to the next model. No retries-with-delay loops — just instant failover. Results before/after: facebook/react scan → large fraction of llm 503 errors, dashboard full of red. {"category","short","priority"} and my parser takes the first {...} block, tolerating markdown noise. Small models return sloppy JSON — the contract still wins.Free models are slower and sometimes dumber than paid ones. For {category, short, priority} — a constrained classification task — the difference is irrelevant. For open-ended reasoning, it isn't. Match the model class to the task. If you're building agents on free tiers: your first engineering task isn't the prompt — it's failover. Rotate, parse defensively, and design for 503s. Then the free tier becomes genuinely free, and your demo stops breaking mid-scan. I put the whole thing agent loop + rotation + no-framework dashboard in a public repo: github.com/pyfile-toolkit/agent-triage. Have fun.