How to Get Powerful AI for Free: A Roundup of APIs That Don't Ask for Money

I run LLMs every day — in nanobots, in my code editor, in my own scripts. And I know how fast a paid API counter turns into a line item. The good news: a large chunk of that load can be taken off for free. Not a “14-day trial”, but genuinely permanent free tiers that providers keep open — Google, Groq, Cerebras, Mistral, NVIDIA and a dozen more.

I gathered and tested this arsenal. Below — what actually works, what each tool is best for, how to plug it in within five minutes, and where the pitfalls hide. One caveat up front: I take the exact limits and models from a living source (more on that below), and compatibility and geo — from my own practice.

What this list is

There is one GitHub repository that has become the de facto standard on this topic: free-llm-api-resources — nearly 26 thousand stars, 2.7 thousand forks, and, crucially, it auto-updates. It is an aggregator of free LLM inference APIs with exact limits: how many requests per minute, per day, how many tokens. The genuinely free providers are listed separately — not the ones that hand you a starter credit and then send a bill.

I pulled from it the top that makes sense for real work, and added my own notes from practice.

Top providers, from practice

⚡ Groq — when speed matters

Groq runs on its own hardware (LPU) and delivers inference at lightning speed. Models — Llama 3.1 8B, Llama 3.3 70B, Llama 4 Scout, Qwen, plus Whisper for speech recognition. The limit is generous: for example, Llama 3.1 8B — 14,400 requests per day. That can be enough for a whole farm of bots on light tasks. The constraint is a modest tok/min, so long walls of text fare worse than short quick replies. OpenAI SDK compatible. Needs a key.

What I use it forResponsive conversations where the user is waiting for an answer right here, right now.

⚡ Cerebras — the fastest on the market

Even faster than Groq. Offers GPT-OSS-120B and Llama 3.1 8B. Limits: 30 req/min, 14,400 per day, 60k tokens/min. OpenAI SDK compatible. In places there's a waitlist. If you need maximum responsiveness on a large model — this is the one.

What I use it forFast answers where 8B is not enough and you can't afford to wait.

⭐ Google AI Studio — the best quality for free

Gemini Flash (3.5 / 3 / 2.5) plus Flash-Lite and the Gemma line. Quality — top shelf among the free options. There's an OpenAI-compatible endpoint (/openai/). But they throttle by volume: Gemini 3.5 Flash — 5 req/min and only 20 requests per day per key. So it's not the “main stream” but the “when you really need a smarter head”.

An important caveat: outside the UK / Switzerland / EEA / EU your data goes toward training. For public and internal tasks — fine; for sensitive client data — no.

⭐ Mistral (La Plateforme) — the fattest limit

Now this is interesting: 1 billion tokens per month for free. Plus 1 req/sec and 500k tokens/min. All Mistral models, open and proprietary. OpenAI compatible. This is a real alternative to a paid API for the bulk of your volume.

The catch: mandatory consent to training on your data and phone verification. So again — not suitable for sensitive content, but an excellent option for high-volume flow.

NVIDIA NIM — a wide choice of open models

Lots of open models, 40 req/min, OpenAI compatible. Needs phone verification, there are context limits. A good backup runway.

More from the list — as the situation calls

• OpenRouter (free models) — Llama 3.3 70B, Hermes 3 405B, DeepSeek and others. 20 req/min, but only 50 per day on the shared quota (up to 1000/day after a $10 top-up). If you're already there — moving part of your load onto the free models cuts spend immediately.
• Cloudflare Workers AI — Gemma, Llama, Mistral, Qwen; 10,000 “neurons” per day (their own abstract unit, not tokens). Logical if you're already on Cloudflare.
• Cohere — Command A, Aya; 1000 requests per month, but its own SDK, not OpenAI.
• Mistral Codestral — tuned for code, 2000 req/day. They warn you honestly: “free for now”, later moved to a subscription.
• GitHub Models, HuggingFace Inference, Scaleway, Alibaba Qwen — they exist, but either with hard limits or essentially a generous trial.

How to plug it in within five minutes

Almost all of the above (except Cohere) are compatible with the OpenAI SDK. Which means: you don't touch the code at all. You change two fields — the address and the key.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.groq.com/openai/v1",   # endpoint провайдера
    api_key="ВАШ_КЛЮЧ",
)

resp = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[{"role": "user", "content": "Привет!"}],
)
print(resp.choices[0].message.content)

In Cursor and Claude Code — same thing: in settings you drop in your base URL and key, and the editor starts calling the free endpoint. That's it, you're working.

Pitfalls — read before you integrate

1. Limits are a wall. Gemini — 20 requests a day. Cohere — 1000 a month. A single provider won't carry production. The solution — a router with fallback: the main stream onto the fat limits (Mistral, Groq), quality/peaks onto Gemini, and keep the paid tier only for what genuinely requires a top model.
2. “Free for now.” Codestral openly promises to move to a subscription. Don't build a critical service on a single such tier — keep a spare.
3. Data goes toward training. On most free tiers (Google outside the EU, Mistral — mandatory, and several others) your requests are used for training. For public and internal tasks — fine. For client data with sensitive information — only a paid tier or self-host. This isn't a trifle, it's a matter of trust.
4. Geography. The list is US-centric, but in practice the Groq, Cerebras, Mistral and Google keys work from our region too. With Google outside the EU — access is there, but remember the training on data.

The takeaway

Free AI today isn't a toy but a working tool. Groq and Cerebras cover speed, Gemini Flash — quality, Mistral — volume (a billion tokens a month, think about that). Set up the right router — and you pay only for what is genuinely worth it.

I keep this list bookmarked and check it before every integration — it's alive, it updates, models and limits change. Link: github.com/cheahjs/free-llm-api-resources.

Test, plug in, save. And invest what you save where AI genuinely brings in money.