I've spent the last few weeks wiring free LLM APIs into side projects, and the landscape in 2026 is genuinely better than most tutorials admit — but the limits are also where every "free forever" blog post quietly dies. Here's my field notes: what each free tier actually gives you, where the gotchas are, and the workflow I use to keep them straight.
The shortlist that actually works
Groq is still the speed king. The free tier gives you an OpenAI-compatible endpoint, and tool-calls work on Llama-class models. The rate limits are per-minute and generous enough for a demo, but sustained polling will get you 429s fast.
Gemini has the most generous free quota of the big providers, and the API is OpenAI-compatible now, which means you can swap it in with a one-line base-URL change. Watch out for the per-day caps if you're building anything that users hammer.
Mistral's free tier (La Plateforme) is real but region-gated and identity-verified. If you're in a supported region, it's a solid workhorse for structured output.
