Free $300 AI credits — every provider, no card required
· Insights
$3,000+ of free AI credits across 10 providers, no credit card required. Google, Hugging Face, Modal, Groq, Cohere, Mistral, OpenRouter — stack them for 6+ months.
$3,000+ of free AI credits across 10 providers, no credit card required. I tested every free tier I could find over 30 days. Here's the ranked list, what each gives you, and how to stack them for 6+ months of development.
The list — ranked by usefulness
Total: ~$3,000+ in free credits, plus free tiers on 6 providers that never expire.
Provider deep-dives
Google AI Studio — the workhorse
Gemini 1.5 Flash is free for low-volume use (15 requests/minute, 1,500/day). That's enough for most personal projects and prototyping.
The catch: Google logs your prompts for training (unless you opt out in settings). Don't use for sensitive data.
Hugging Face — the open-model haven
Free CPU inference on 100,000+ models. No rate limits if you use the free tier politely. Paid Inference Endpoints start at $0.06/hour for GPU.
Best for: experimenting with models before paying for production. I run all my model evaluations here first.
Modal — the serverless GPU king
$30/month free forever, no card required. Run Python functions on GPU without managing infrastructure:
@app.function(gpu="T4") def generate(prompt: str): from transformers import pipeline pipe = pipeline("text-generation", model="meta-llama/Llama-3.1-8B-Instruct") return pipe(prompt)
The $30/month covers ~50 hours of T4 GPU time. Enough for prototyping and small batch jobs.
Groq — the speed demon
Groq runs Llama 3.1, Mixtral, and Gemma on custom LPU hardware. Speeds of 500-800 tokens/sec — faster than any other provider.
Free tier: 30 requests/minute, 14,000 requests/day. The rate limits are generous — I've never hit them in personal use.
Cohere — for embeddings + reranking
Cohere's free tier (1,000 calls/month) is the best for RAG pipelines:
# Embed embeds = co.embed(texts=["hello", "world"], model="embed-english-v3.0")
# Rerank results = co.rerank( query="how to ship a Tauri app", documents=[{"text": "Tauri build guide..."}], model="rerank-english-v3.0", )
Use this for semantic search in your apps. Embeddings are $0.10/1M tokens if you exceed free tier.
OpenRouter — one key, every model
OpenRouter aggregates 200+ models from OpenAI, Anthropic, Google, Mistral, Meta, etc. One API key, one billing surface.
Free models on OpenRouter: - Llama 3.1 8B / 70B (free) - Mistral 7B Instruct (free) - Gemma 2 9B (free) - Qwen 2.5 7B (free)
The free models have rate limits but they're real — no quality degradation, no logging (per their privacy policy).
How to stack them
I run all my personal projects on this stack:
1. Prototyping: Groq (free, fast) or Gemini Flash (free, generous limits) 2. Production single calls: Modal ($30/mo free, full control) 3. Agentic workflows: OpenRouter free models for experimentation, paid for production 4. Embeddings: Cohere free tier (1k calls/month covers most side projects) 5. Model evaluation: Hugging Face (free CPU inference on 100k+ models)
Total monthly cost: $0, until I outgrow free tiers.
The catch — what "free" actually means
Every provider logs something. Read the fine print: