Stop Paying for AI: 100+ Premium Models You Can Use for Free

You are paying for AI you don't need to pay for.

$20/month for ChatGPT.

$20/month for Claude.

$20/month for Cursor.

$20/month for Gemini.

$80/month to access models you could be running for free.

I spent 3 days mapping every legitimate free tier, free API, free credit, and free self-hosted model that exists right now.

Here is the complete map.

No credit card. No trial traps. No expiring free tier that bills you at 2am.

Save this. It will save you hundreds per year.

First — understand the two types of "free"

There are two completely different things people call "free AI."

Type 1: Someone else runs it, you call it.

Google, Groq, Mistral, OpenRouter hand you an API key at zero cost. You get rate limits. You get real frontier models. You give up your prompts — most free tiers train on what you send.

Type 2: You download the weights and run it yourself.

Fully private. Nothing leaves your machine. You pay in electricity and VRAM instead of data or dollars.

These are not variations on a theme. They are opposites.

Choose based on what matters more to you: convenience or privacy.

The master list of free hosted APIs

These give you a real API key. No credit card. No 24-hour trial trap. Real models. Real rate limits. Real forever.

1. Google AI Studio

The best free access to a frontier model that exists right now.

→ ~1,500 requests/day on Gemini Flash. Resets daily.
→ 1M context window
→ Handles images and PDFs
→ Zero credit card. Zero expiry.

Go to: aistudio.google.com -> Sign in with Google. Copy API key. Done.

Important: free-tier prompts may train Google's models. Keep sensitive data off.

2. Groq

Fastest free inference alive.

300+ tokens per second on open-weight models. Llama, Qwen, Kimi — all running on custom LPU hardware.

→ ~30 req/min, 1,000/day on a 70B model
→ Clear no-training policy
→ OpenAI-compatible endpoint

You swap one base URL and your existing tools work instantly.

Go to: console.groq.com

3. Mistral (La Plateforme)

1 billion free tokens on signup.

→ Mistral Large 3 (competes with Claude Opus 4.7)
→ Codestral (beats GPT-5.5 on coding benchmarks)
→ Mistral Medium 3.5
→ Pixtral Large (vision)
→ 256K context windows
→ OpenAI-compatible

Setup:

# Step 1: Sign up at console.mistral.ai (no card)
# Step 2: Grab your API key
# Step 3: Test it

curl https://api.mistral.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistral-small-latest",
    "messages": [{"role": "user", "content": "Hi"}]
  }'

# Step 4: Swap base URL in any tool
# Replace: https://api.openai.com/v1
# With:    https://api.mistral.ai/v1

Important: the free Experiment tier requires opting into training.

Go to Settings → Data Training → disable if you want privacy.

4. OpenRouter

One API key. 25+ permanently free models.

Filter with the :free suffix in any model name. No credit card. No expiry.

Models available free:

→ Llama 3.3 70B

→ DeepSeek V3

→ Qwen3

→ Mistral 7B

And 20+ more rotating in

Go to: openrouter.ai

5. Cerebras

Faster than Groq for some workloads.

Wafer-scale chip inference. Qwen3 235B at serious speed.

→ Generous free tier

→ Explicit no-training policy

→ OpenAI-compatible

Go to: cloud.cerebras.ai

6. GitHub Models

Free if you have a GitHub account.

→ GPT-4o

→ GPT-4.1

→ Llama 4

→ Mistral

→ DeepSeek

Rate-limited but free forever within dev use.

Go to: github.com/marketplace/models

7. Cloudflare Workers AI

10,000 "neurons" per day free.

Good for serverless apps. Edge inference — runs close to your users.

→ Kimi K2

→ GLM-4.7 Flash

→ gpt-oss

→ Granite 4

Go to: developers.cloudflare.com/workers-ai

8. Hugging Face Inference

Thousands of models. Serverless inference. No credit card.

Best for trying unusual or brand-new models. Rate limits are tight. Cold starts happen.

Go to: huggingface.co/inference-api

The hidden free credits most people miss

These are not permanent free tiers. They are one-time or promo credits that are large enough to matter.

AWS Bedrock: $200 free credits

Every new AWS account gets $200 in free credits.

You can use them on:

→ Claude Opus 4.8

→ Claude Opus 4.7

→ Claude Sonnet 4.6

→ Claude Haiku 4.5

How to get it:

What $200 gets you:
→ Millions of tokens on Haiku (cheapest)
→ Hundreds of thousands on Sonnet
→ Tens of thousands on Opus

Tip: Use Haiku for simple tasks (10-20x cheaper than Opus), Opus only for hard reasoning.

AgentRouter: $100 free credits

Non-profit AI gateway. One API key, one base URL, 30+ models.

→ Claude Sonnet 4.5

→ GPT-4o

→ DeepSeek R1 + V3

→ GLM-4.5

→ Qwen3

→ Gemini 2.0 Pro

# For Claude Code specifically:
export ANTHROPIC_BASE_URL=https://agentrouter.org
export ANTHROPIC_API_KEY=your-key
claude

Privacy note: China-based gateway, Singapore infra. Not for sensitive work. Good for: side projects, learning, prototypes.

b.ai: 500K free credits

500,000 credits on signup. No verification needed.

→ DeepSeek V4 Pro and Flash → Gemini 3.5 Flash → MiniMax M3

When you run out: yourname+1@gmail.com, yourname+2@gmail.com etc. Each Gmail variant gets 500K fresh credits. There is also a 1:1 top-up bonus up to $100 if you deposit.

Runtime by Bad Theory Labs: 10M free tokens/month

10 million tokens per month. No credit card. Just Google login.

→ Claude Opus 4.8 → GPT 5.5 → DeepSeek V4 Pro and Flash → GLM 5.2 → Kimi K2.6 → Gemini → 340+ models total

Works in Cursor, Aider, Claude Code, LangChain — anything OpenAI-compatible.

Note: launch promo. Free credits will likely reduce once they hit scale.

OpenAI Data Sharing Program: 250K tokens/day

This is buried inside OpenAI's platform settings.

Most people have no idea it exists.

→ 250K tokens/day for GPT-5.5 and GPT-5.2
→ 2.5M tokens/day for Mini and Nano variants
→ Resets every single day

Important:
→ Your data gets used by OpenAI for training
→ Don't use for client work or sensitive data
→ Requires a positive account balance to activate
→ Perfect for personal builds and learning

OpenAI Codex Program: $1,200 in ChatGPT Pro

6 months of ChatGPT Pro free. For developers with an active GitHub.

The bar is lower than people think. Active commits. A few repos with stars. Basic activity counts.

Apply at: openai.com/form/codex-for-oss

Worst case: they say no. Best case: $1,200 of tools for free.

Chinese frontier models — all free

5 models that rival GPT and Claude. All free right now. One NVIDIA key unlocks all of them.

The models:

→ DeepSeek V4 Flash — fastest inference, cheapest pricing alive
→ MiniMax M3 — 1M context, coding, SWE-Bench Pro 59% (ahead of GPT-5.5)
→ Qwen3.5-397B — complex reasoning, keeps up with frontier
→ Kimi K2.6 — agentic workflows, 1 trillion parameters
→ GLM 5.1 — solid all-rounder for daily AI work

Setup via NVIDIA API (2 minutes):

# Step 1: Sign up at build.nvidia.com
# Phone verify required. No credit card.

# Step 2: Get your key
# API section → Generate nvapi- key

# Step 3: Point any client at NVIDIA
# Base URL: https://integrate.api.nvidia.com/v1

# Step 4: Use any model
curl https://integrate.api.nvidia.com/v1/chat/completions \
  -H "Authorization: Bearer nvapi-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek/deepseek-v4-flash",
    "messages": [{"role":"user","content":"Hello"}]
  }'

# All model names:
# deepseek/deepseek-v4-flash
# minimaxai/minimax-m3
# qwen/qwen3.5-397b-a17b
# moonshotai/kimi-k2.6
# zhipuai/glm-5.1

Works in Claude Code, Cursor, Cline, Aider. One key covers 100+ models in the NVIDIA catalog. ~40 req/min rate limit. Fine for daily use.

GLM 5.2 for free — the model beating GPT-5.5 on coding

GLM 5.2 just scored 62% on SWE-Bench. GPT-5.5 scored 58.6%.

Open weights. MIT license. 744B MoE.

Option 1: ZCode IDE (3M tokens/day free)

Zhipu's official coding IDE. GLM 5.2 built in as the default model.

→ 3 million free tokens every single day → 1M context window → Not a trial. Resets daily.

Option 2: Zenmux API (free trial window)

One repo that lists everything

awesome-free-models by 12britz.

Motto: "Running AI shouldn't require a credit card."

What it contains:

→ 30+ open-weight models you can self-host
→ 50+ free API providers — zero credit card, zero trial traps
→ Local inference tools (Ollama, llama.cpp, vLLM)
→ Chatbot UIs with genuine free tiers
→ Coding assistants, CLI tools, RAG frameworks
→ Agentic frameworks and fine-tuning playgrounds

All organized by category. 300 links. Every one tested.

What this replaces:
→ API discovery services: $50-100/mo
→ 20+ tabs comparing free tiers
→ Newsletter subscriptions: $30/mo for resource roundups

Go to: github.com/12britz/awesome-free-models

One router to rule them all: FreeLLMAPI

16 free providers. ~1.7 billion tokens per month. One endpoint.

FreeLLMAPI is an open-source self-hosted proxy that:

→ Stacks free tiers from Google, Groq, Cerebras, Mistral, OpenRouter, GitHub, Cloudflare, HuggingFace, and 8 more
→ Auto-routes to whichever provider isn't rate-limited
→ Falls over automatically on 429s
→ Tracks per-key usage so you stay under every cap
→ OpenAI-compatible AND Anthropic-compatible

One base URL. Your existing tools work instantly.

from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:3001/v1",
    api_key="freellmapi-your-unified-key",
)

# Auto-picks the best available free model
resp = client.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "What is RAG?"}],
)
print(resp.choices[0].message.content)
print("Routed via:", resp.headers.get("x-routed-via"))

For Claude Code specifically:

export ANTHROPIC_BASE_URL=http://localhost:3001
export ANTHROPIC_AUTH_TOKEN=freellmapi-your-unified-key
claude
# Now Claude Code routes through your free pool
Docker setup (one command):
bash
curl -fsSL https://freellmapi.co/install.sh | bash
# Opens at http://localhost:3001
# Add your provider keys
# Start routing

Go to: github.com/tashfeenahmed/freellmapi

Self-hosting: run models on your own machine

No API key needed. No rate limits. Fully private.

You just need RAM.

How much RAM do you need?

Rule: ~0.6 GB of RAM per billion parameters (at standard 4-bit quantization).

The easiest path: Ollama

# Install (Mac/Linux/Windows)
curl -fsSL https://ollama.com/install.sh | sh

# Run any model (downloads automatically)
ollama run qwen3:8b          # 5.5GB, great all-rounder
ollama run llama3.3:70b      # 40GB, near-frontier quality
ollama run mistral:7b        # 5GB, fast and capable
ollama run deepseek-r1:14b   # 9GB, strong reasoning
ollama run phi4:14b          # 9GB, punchy Microsoft model

# It auto-serves an OpenAI-compatible API at:
# http://localhost:11434/v1
# Plug into any tool immediately

20 best open-weight models to self-host

Sorted by what actually matters: license and hardware.

Truly free to use commercially (Apache 2.0 / MIT):

→ Qwen3 (Alibaba) — most versatile. 0.6B to 200B+. Apache 2.0.
→ DeepSeek-R1 (DeepSeek) — reasoning-heavy. MIT. Distills from 7B to 70B.
→ GLM (Zhipu) — MIT. Leads coding benchmarks at the large end.
→ gpt-oss (OpenAI) — Apache 2.0. Their open-weight family. 20B sweet spot.
→ Mistral / Devstral — Apache 2.0. Devstral for coding agents specifically. → Phi-4 (Microsoft) — MIT. Small but punchy. Phi-4-mini runs on any laptop.
→ OLMo (Allen AI) — Apache 2.0. One of the only truly open-source models (weights + training data + code, all public).
→ Granite (IBM) — Apache 2.0. Enterprise and RAG focused.

Open-weight with some conditions:

→ Llama 3.x (Meta) — open-weight but not truly open-source. 700M MAU cap (rarely relevant). Best: 8B (entry) to 70B (power).
→ Gemma 4 (Google) — license restricts using it to train competing models. 12B fits in 16GB. Good vision support.
→ Falcon-H1 (UAE) — 256K context. Royalty kicks in above $1M revenue. → Command R (Cohere) — non-commercial only. Fine for personal use.

Big ones that need datacenter hardware:

→ Kimi K2 (Moonshot) — 1T params. Genuinely frontier coding. Needs 550GB+.
→ MiniMax M3 — multimodal, 1M context. Datacenter only.
→ DeepSeek V4/R1 (full) — 671B MoE. ~370GB. Not for home use.

The complete free AI toolkit

Everything you need. Nothing you pay for.

Daily use (no GPU needed):
→ Google AI Studio — frontier model, 1,500 req/day
→ Groq — fastest inference, open models
→ OpenRouter — widest variety, 25+ free models

One-time credits to claim now:
→ AWS Bedrock — $200 to use on Claude
→ AgentRouter — $100, 30+ models
→ Runtime BTL — 10M tokens/month
→ b.ai — 500K credits, refresh with Gmail aliases

For developers using agents and code editors:
→ NVIDIA API — one key, 100+ models including GLM and Kimi
→ ZCode IDE — 3M tokens/day on GLM 5.2
→ FreeLLMAPI — self-hosted router, 1.7B tokens/month total

Self-hosting (privacy-first):
→ Ollama — simplest CLI, one command
→ LM Studio — GUI, model browser, local API
→ Best models: Qwen3 8B, Mistral 7B, Phi-4

The master directory:
→ awesome-free-models on GitHub — 300 verified links

The hidden cost of "free" hosted tiers

Read this before using any free hosted API in production.

Most free tiers train on your prompts.

That means: your code, your business logic, your user data — all potentially in someone's next training run.

The ones with explicit no-training policies:

→ Groq: clear no-training policy
→ Cerebras: explicit no-training
→ GitHub Models: scoped to development use
→ Self-hosted: 100% private by definition

The ones you should keep sensitive data off:

→ Google AI Studio (free tier may train)
→ Mistral Experiment tier (opt-in to training required)
→ HuggingFace Inference (standard T&C)

Rule: if the prompt contains client data, credentials, or anything you wouldn't want in a training dataset — self-host or pay for a privacy-first tier.

Start in 5 minutes

Pick the one that fits your situation:

"I just want to try frontier models with zero setup"
→ Go to aistudio.google.com. Sign in with Google. Done.

"I need the fastest possible inference for an agent"
→ Groq. console.groq.com. API key in 2 minutes.

"I want Claude for free"
→ AWS Bedrock. $200 credits. Follow the setup above.

"I want 100+ models with one key"
→ NVIDIA API. build.nvidia.com. Phone verify, no card.

"I need privacy. Nothing leaves my machine."
→ curl -fsSL https://ollama.com/install.sh | sh→ ollama run qwen3:8b→ Done. Fully local. Fully private.

"I want everything stacked automatically"
→ FreeLLMAPI. One Docker command. 16 providers. 1.7B tokens/month.

The gap between what people pay for AI and what AI actually costs to access is growing every month.

$80/month was reasonable when this was all locked up.

It is not locked up anymore.

Every tool in this article is live right now.

If this saved you money:

→ Repost so other builders stop overpaying
→ Follow @sairahul1 for more finds like this
→ Bookmark this — free tiers change, come back to check

I write about AI tools, building products, and systems that run while you sleep.

All links:

→ Google AI Studio: aistudio.google.com
→ Groq: console.groq.com
→ Mistral: console.mistral.ai
→ OpenRouter: openrouter.ai
→ Cerebras: cloud.cerebras.ai
→ GitHub Models: github.com/marketplace/models
→ NVIDIA API: build.nvidia.com
→ AWS Bedrock: aws.amazon.com
→ AgentRouter: agentrouter.org
→ Runtime BTL: runtime.badtheorylabs.com
→ b.ai: b.ai
→ ZCode IDE: zcode.z.ai
→ Zenmux: zenmux.ai
→ FreeLLMAPI: github.com/tashfeenahmed/freellmapi
→ Ollama: ollama.com
→ awesome-free-models: github.com/12britz/awesome-free-models
→ OpenAI Data Sharing: platform.openai.com/settings/organization/data-controls
→ OpenAI Codex: openai.com/form/codex-for-oss