The Ultimate List of Free AI APIs in 2026, No Credit Card Needed
The Ultimate List of Free AI APIs in 2026, No Credit Card Needed
┌──────────────────────────────────────────────────────────┐
│ │
│ THE ULTIMATE LIST OF FREE AI APIs IN 2026 │
│ No Credit Card Needed │
│ │
│ ██████████████████████████████████████████████████ │
│ Google AI Studio · Groq · OpenRouter · Mistral │
│ Cerebras · Cohere · HuggingFace · GitHub Models │
│ DeepSeek · SambaNova · NVIDIA NIM · Cloudflare │
│ ██████████████████████████████████████████████████ │
│ │
│ 20+ Free Providers Tested & Verified │
│ as of 2026 │
└──────────────────────────────────────────────────────────┘
Here is something most people do not realize: you can run some of the most powerful AI models on the planet right now, today, without entering a single credit card number.
Not trial tricks. Not bait-and-switch free tiers that bill you the moment you forget to cancel. Actual, usable, developer-ready AI APIs at zero cost.
Back in 2023, getting API access to a serious language model meant setting up billing, budgeting carefully, and hoping your prototype did not rack up an unexpected bill overnight. That world is gone. In 2026, more than twenty providers offer free access to frontier-level models, and some of them are genuinely generous.
This guide breaks down every single one. Who offers what, what the limits actually are, whether you need a payment method, and which provider fits which type of project. If you have been putting off building something because you thought AI APIs were too expensive, this is going to change your mind.
What “Free” Actually Means Here
Before getting into the list, it is worth being clear about the different kinds of “free” you will encounter.
Truly free tiers give you an API key, rate limits, and no expiration date. No card required. The service just stops working when you hit the limit and resets the next day or month.
Trial credits give you a dollar amount upfront, usually $5 to $25, that eventually runs out. Still useful, especially for testing models you cannot get any other way, but they are not permanent.
Chat-only free access is what most people think of when they hear “free AI.” You get a web interface, not an API. Useful for personal tasks, not for building apps.
The providers below are organized by which category they fall into. The specific numbers mentioned are accurate as of early 2026, but these limits shift frequently. Always double-check the official docs before planning anything around specific quotas.
The Full Comparison at a Glance
| Provider | Top Models | Rate Limit | Daily/Monthly Cap | Card Required |
|---|---|---|---|---|
| Google AI Studio | Gemini 2.5 Pro, 2.5 Flash | 5-15 RPM | 250K TPM | No |
| Groq | Llama 3.3 70B, Llama 4 Scout | 30-60 RPM | 1K req/day (70B) | No |
| OpenRouter | DeepSeek R1, Llama 4, Qwen3 | 20 RPM | 50 req/day | No |
| Mistral AI | Large, Small, Codestral | 2 RPM | 1B tokens/month | No |
| Cerebras | Llama 3.3 70B, Qwen3 32B | 30 RPM | 1M tokens/day | No |
| Cohere | Command R+, Embed 4 | 20 RPM | 1K req/month | No |
| Cloudflare Workers AI | Llama 3.2, Mistral 7B | N/A | 10K neurons/day | No |
| GitHub Models | GPT-4o, o3, Grok-3 | 10-15 RPM | 50-150 req/day | No |
| NVIDIA NIM | DeepSeek R1, Kimi K2.5 | 40 RPM | 1K credits | No |
| HuggingFace | 300+ community models | Varies | Small monthly credits | No |
| xAI | Grok 4, Grok 4.1 Fast | Varies | $25 signup credits | No |
| DeepSeek | DeepSeek V3, R1 | No hard limit | 5M tokens free | No |
| SambaNova | Llama 3.3 70B, Qwen 2.5 72B | 10-30 RPM | $5 credits + free tier | No |
| Fireworks AI | Llama 3.1 405B, DeepSeek R1 | 10 RPM | Limited without card | No |
| Together AI | Llama 4, DeepSeek R1 | Dynamic | No free tier ($5 min) | Yes |
| AI21 Labs | Jamba Large, Jamba Mini | 200 RPM | $10 credits/3 months | No |
Tier 1: The Real Deal, Free Forever
These are the providers you want to know about first. No credit card, no expiry, no tricks. You sign up, get a key, and start building.
Google AI Studio
If you only sign up for one thing on this list, make it Google AI Studio.
You get access to Gemini 2.5 Pro, Gemini 2.5 Flash, and Gemini 2.5 Flash-Lite, all on the free tier. These are not stripped-down demo versions. They are the same models that compete directly with GPT-4o and Claude Sonnet in benchmarks.
The context window on Gemini 2.5 Pro is 1 million tokens. That means you can paste in an entire codebase, a full book, or hundreds of documents and the model processes all of it in one call. For most developers, that alone changes how you think about what is possible.
The API is OpenAI-compatible too, which is a big deal practically. If you already have code pointing at OpenAI's API, you swap the base URL and your API key and it just works. No rewriting.
Multimodal inputs are included at no extra cost. Send images, audio clips, or video alongside your text prompts. This is not gated behind a paid plan.
Google did tighten the free quotas in late 2025, so the numbers are a little lower than they used to be. But they are still the most generous by total token volume of any provider on this list.
Limits: Gemini 2.5 Pro runs at 5 RPM with 100 requests per day. Flash is 10 RPM with 250 per day. Flash-Lite is 15 RPM with 1,000 per day. The shared cap across all models is 250,000 tokens per minute.
Best for: Pretty much everything. Prototyping, building real apps, working with long documents, multimodal projects.
How to start: Go to ai.google.dev, sign in with any Google account, and generate an API key. Takes about two minutes.
Groq
Groq's entire pitch is speed, and they deliver on it.
Their custom LPU (Language Processing Unit) hardware runs inference at over 300 tokens per second. To put that in perspective, most cloud GPU providers run somewhere between 40 and 80 tokens per second. On Groq, responses that would take several seconds elsewhere come back almost instantly.
For interactive apps, customer-facing features, or anything where latency actually matters to the user experience, this difference is real. When a user asks a question and gets an answer in half a second instead of three seconds, it feels like a completely different product.
The free tier includes Llama 3.3 70B, Llama 4 Scout, Qwen3 32B, Kimi K2, and a handful of other open-source models. Smaller models like Qwen3 32B get 60 requests per minute. Larger ones like the 70B models get 30 RPM.
The daily request cap is the thing to watch. You get 1,000 requests per day on the 70B-class models, which sounds like a lot but goes fast if you are testing something heavily. The 8B models get 14,400 requests per day, which is genuinely large.
Limits: 30 RPM on 70B models (60 RPM on smaller models), 12,000 tokens per minute, 1,000 requests per day for large models or 14,400 for small ones. All limits are at the organization level.
Best for: Real-time features, chat applications, anything where the user is waiting for a response.
How to start: Sign up at console.groq.com. API key is ready immediately. Endpoint is OpenAI-compatible.
OpenRouter
OpenRouter is not really a model provider. It is a router that sits in front of dozens of providers and gives you one unified API key to access all of them.
The free tier works through a community-funded model. Users who have paid accounts subsidize a pool of free credits that the whole community draws from. This means you can access free variants of models from Meta, Google, Mistral, and others through a single endpoint.
The model variety is unmatched. Free models at the time of writing include DeepSeek R1 and V3, Llama 4 Maverick and Scout, Qwen3 235B, and others. Free model variants are labeled with a :free suffix in the model list.
If you want to build something that compares outputs from different models, or lets users choose their preferred model, OpenRouter makes that trivially easy. One API key, one endpoint, unlimited model switching.
The free tier gives you 50 requests per day without any account balance. If you load $10 or more onto your account, that jumps to 1,000 per day.
Limits: 20 RPM on free models, 50 requests per day without a balance, 1,000 per day with $10+ balance.
Best for: Comparing models, building model-agnostic apps, accessing a wide variety of models without managing multiple accounts.
How to start: Create an account at openrouter.ai. The API format is identical to OpenAI's.
Mistral AI
Mistral is a French AI company and their model quality is legitimately excellent. The free “Experiment” tier on their La Plateforme API covers every Mistral model: Large, Small, Codestral, Pixtral 12B, embedding models, and even their OCR model.
The rate limit is the painful part. Two requests per minute is restrictive. You can still do useful things in development, but you will need to add delays between calls if you are doing any kind of batch processing.
What makes up for it is the monthly volume cap: 1 billion tokens per month. That is an enormous amount of usage for free. If your application makes careful, infrequent calls, Mistral's free tier goes very far.
Codestral deserves a special mention. It is Mistral's code-focused model, and it performs genuinely well on programming tasks. For someone building a coding assistant or a tool that generates and explains code, Codestral is worth testing seriously.
Le Chat, Mistral's web interface, is also free for personal use and has more generous limits than the API tier. If you only need occasional AI assistance and not programmatic access, Le Chat might serve you better than fighting the 2 RPM limit.
Limits: 2 RPM, 500,000 tokens per minute, 1 billion tokens per month on the Experiment tier.
Best for: Code generation, projects with European data residency requirements, teams that want access to the full Mistral model lineup.
How to start: Sign up at console.mistral.ai. Le Chat is at chat.mistral.ai.
Cerebras
Cerebras runs inference on their wafer-scale engine, a chip design that is fundamentally different from how NVIDIA GPUs work. The practical result is inference speed that they claim is 20 times faster than GPU-based providers.
The free tier includes Llama 3.3 70B, Qwen3 32B, Qwen3 235B, and OpenAI's open-source GPT-OSS 120B. You get 30 requests per minute and 1 million tokens per day.
One use case where Cerebras shines is agentic workflows. When you are building an AI agent that needs to call a model 15 or 20 times in sequence, the wall-clock time for the whole workflow depends heavily on how fast each individual call is. At Groq or Cerebras speeds, a 20-step agent run that would take 60 seconds on a standard GPU provider completes in under 10.
No waitlist, no invite required. Sign up and start calling the API.
Limits: 30 RPM, 60,000 tokens per minute, 1 million tokens per day.
Best for: Multi-step agent workflows, speed-critical applications, development where you want fast iteration cycles.
How to start: Sign up at cloud.cerebras.ai. OpenAI-compatible API.
Cohere
Cohere's free tier is built specifically for RAG applications, and it is the most complete free stack for that use case anywhere.
RAG stands for Retrieval-Augmented Generation. It is the technique where you give an AI model access to external documents or a knowledge base, and it uses those documents to answer questions accurately instead of making things up from memory. It is how you build a chatbot that actually knows about your company's documentation, or a search tool that gives real answers instead of keyword matches.
Cohere's free tier covers the full pipeline: Command R+ for text generation, Embed 4 for turning documents into vectors you can search, and Rerank 3.5 for ranking search results by relevance. That is everything you need for a production-grade RAG system, all from one provider, all at no cost.
The monthly cap is the constraint. You get 1,000 API calls per month across all services combined. That is enough to build and test a proof of concept but not enough for a high-traffic production app.
The free tier is also restricted to non-commercial use, so if you are building something you plan to sell, factor that in.
Limits: 20 RPM, 1,000 requests per month. Non-commercial use only on the free tier.
Best for: Document search, question-answering over knowledge bases, anything involving embeddings and retrieval.
How to start: Sign up at dashboard.cohere.com. Trial keys are generated instantly.
Cloudflare Workers AI
Cloudflare's approach is completely different from every other provider on this list. Their AI runs at the edge, meaning inference happens on servers distributed all over the world, close to wherever your users are.
The free tier comes bundled with Cloudflare Workers (their serverless platform) at no cost. You get 10,000 neurons per day. A neuron is Cloudflare's unit of compute, and it maps loosely to tokens processed.
The model catalog includes Llama 3.2 variants, Mistral 7B, FLUX.2 for image generation, and Whisper for speech-to-text. The models are quantized for edge deployment, meaning they are optimized for speed and smaller memory footprint. Quality is very good but may differ slightly from full-precision versions running on data center hardware.
The edge deployment means something practically important for user-facing applications: low latency for users anywhere in the world. If your users are in Lagos, Seoul, and Sao Paulo, they all get fast responses without you having to manage a multi-region deployment.
Limits: 10,000 neurons per day. No hard RPM limit listed.
Best for: Serverless deployments, apps that need global low latency, combining AI with other edge logic.
How to start: Create a Cloudflare account and enable Workers AI in the dashboard. The free tier activates automatically.
GitHub Models
GitHub Models gives you playground and API access to a curated set of high-quality models. The lineup includes GPT-4o, GPT-4.1, o3, xAI Grok-3, DeepSeek-R1, and others.
The intended audience is developers who want to test models before deciding which one to integrate. The playground interface is well-designed for that purpose: paste in a prompt, switch between models, compare outputs.
Rate limits are organized by model tier. High-capability models like GPT-4o and o1 get 10 RPM and 50 requests per day. Lower-tier models get 15 RPM and 150 per day.
The per-request token limits are 8,000 input tokens and 4,000 output tokens, which is enough for most tasks but will be a constraint if you are working with long documents.
If you are already deep in the GitHub ecosystem and use it for code hosting, project management, or CI/CD, GitHub Models slots in naturally. No new account, no separate dashboard to check.
Limits: 10-15 RPM, 50-150 requests per day depending on model tier. 8K input / 4K output tokens per request.
Best for: Quick model evaluation, developers who live in GitHub, lightweight experimentation.
How to start: Visit github.com/marketplace/models. Available to any GitHub account.
HuggingFace Inference API
HuggingFace hosts hundreds of thousands of community-trained models, and their Inference API lets you call them over HTTP without running any infrastructure yourself.
The free tier has a catch worth knowing about: models are loaded on demand. If a model has not been called recently, it might be “cold,” and your first request could take 30 seconds or more while the model loads onto a server. Popular models stay warm and respond quickly, but niche specialized ones might time out on the first call.
The value is the long tail of models. Need a sentiment classifier trained specifically on tweets? A translation model for a language pair that mainstream providers do not cover? A medical text summarizer? A toxicity detector? HuggingFace probably has it, and the Inference API lets you call it without downloading anything or managing GPU resources.
Free tier usage is rate-limited but the exact limits depend on which model you are calling. The general guidance is that it is suitable for development and testing but not production traffic.
Best for: Specialized and niche models, research tasks, experimenting across an enormous range of model types.
How to start: Sign up at huggingface.co, create a user access token, and find any model's API snippet on its model page.
OpenCode (Honorable Mention)
OpenCode is not a model provider but it deserves a place here because it is the most practical free coding assistant available.
It is an open-source terminal-based tool that connects to AI providers through your own API keys. You bring the key (from Google AI Studio or Groq, both free) and OpenCode handles the coding assistant interface: file editing, terminal commands, multi-turn conversations, context from your codebase.
If you have been eyeing paid coding assistants and wondering if there is a free alternative, the combination of OpenCode plus Google AI Studio's free API gets you very close.
How to start: Install from github.com/opencode-ai/opencode through your package manager.
Tier 2: Free Credits That Eventually Run Out
These providers give you a budget upfront. The money runs out eventually, but the credits are still useful for evaluation, testing specific models, or getting started on a new project.
xAI
xAI gives you $25 in free API credits when you create an account. No credit card required to start.
That gets you access to Grok 4 and Grok 4.1 Fast. Grok 4.1 Fast has a 2 million token context window, one of the longest available from any provider. If you are working on a project that needs to process extremely long documents or maintain very long conversation histories, that context window is genuinely useful.
There is also an option to receive $150 in additional monthly credits if you opt into sharing your data with xAI. That requires a prior $5 spend, but for developers who need more volume, it is worth knowing about.
Limits: $25 one-time credits on signup. No card required to start.
How to start: Sign up at console.x.ai.
DeepSeek
DeepSeek is in a category of its own. You get 5 million free tokens when you sign up, valid for 30 days. After that, the pricing is so low it almost functions as free for development purposes.
DeepSeek V3 costs around $0.14 per million input tokens. DeepSeek R1, their reasoning model that competes with models charging 10 times as much, runs around $0.55 per million input tokens. For context, five dollars of DeepSeek credit lasts longer than most developers' monthly development usage.
The API has no hard rate limit, which is unusual and genuinely useful. The platform tries to serve every request. During peak periods there can be capacity issues, but for normal development work it is reliable.
The API is OpenAI-compatible, so integration is straightforward if you are already familiar with the OpenAI format.
Limits: 5 million free tokens on signup (30-day expiry), then pay-per-use at very low rates. No credit card required initially.
How to start: Sign up at platform.deepseek.com.
SambaNova
SambaNova runs inference on their custom RDU (Reconfigurable Dataflow Unit) hardware and offers a genuinely persistent free tier alongside initial $5 credits.
The model lineup includes Llama 3.3 70B, Llama 3.1 405B, and Qwen 2.5 72B. The rate limits vary: 10 RPM on the larger 405B model, 30 RPM on 8B models. The free tier does not expire after the initial credits are used up, which puts SambaNova closer to Tier 1 in practice.
Speed is the main reason to try it. SambaNova's hardware delivers fast inference times that make it a reasonable alternative to Groq or Cerebras for latency-sensitive work.
Limits: 10-30 RPM depending on model size. $5 credits on signup (30-day expiry), persistent free tier beyond that.
How to start: Sign up at cloud.sambanova.ai.
NVIDIA NIM
NVIDIA NIM gives you 1,000 free API credits when you sign up, with the option to request up to 4,000 more. The model catalog is one of the most varied on this list: DeepSeek R1 and V3.1, Llama variants, Kimi K2.5, AI21 Jamba, and a range of domain-specific models for tasks like molecular biology and image analysis.
The credits do eventually run out, but they cover meaningful testing. NVIDIA also provides Docker containers for self-hosted deployment if you have your own GPU hardware, which is free for NVIDIA Developer Program members. That self-hosted path is worth knowing about if your project eventually needs more control over the infrastructure.
Limits: 1,000 credits on signup (up to 5,000 total by request). 40 RPM.
How to start: Sign up at build.nvidia.com. Credits apply automatically.
Fireworks AI
Fireworks specializes in fast, optimized inference for open-source models. The free tier gives you 10 RPM without any payment method on file, which is enough for prototyping.
The model catalog is strong: Llama 3.1 405B, DeepSeek R1, and hundreds of others. If you add a payment method, the rate limit jumps dramatically to 6,000 RPM, making Fireworks a serious option for production workloads at competitive pricing.
For pure free access without a card, the 10 RPM limit is workable for development but tight.
Limits: 10 RPM without a payment method. Increases significantly with card on file.
How to start: Sign up at fireworks.ai.
AI21 Labs
AI21 gives you $10 in trial credits valid for three months. Their models, Jamba Large and Jamba Mini, use a hybrid Mamba-Transformer architecture that performs especially well on long-context tasks.
The rate limit during the trial is 200 RPM and 10 requests per second, which is among the most generous on this list. The $10 credit goes further than you might expect given how generous the rate limits are.
After the trial expires, billing kicks in. Worth testing if you have a specific need for long-context processing or want to compare Mamba-architecture models against standard transformers.
Limits: $10 trial credits, 3-month validity. 200 RPM, 10 RPS.
How to start: Sign up at studio.ai21.com.
Together AI
Together AI does not have a free tier in the traditional sense. They require a minimum $5 credit purchase to get started, and yes, that requires a card.
They are on this list because they occasionally run signup promotions, and their Startup Accelerator program offers up to $50,000 in free credits for qualifying projects. The model catalog includes Llama 4 Scout, DeepSeek R1, and a wide range of other open-source models at competitive pricing.
If you hit their accelerator program, Together AI becomes one of the most generous providers on this list by a wide margin.
Limits: No free tier. $5 minimum credit purchase. Card required.
How to start: Sign up at api.together.ai.
Tier 3: Free Chat Access, No API
These are worth a quick mention even though they do not give you API access. If you just need AI for personal tasks and are not building anything, these chat interfaces are genuinely capable.
ChatGPT Free gives you GPT-5.2 with daily message limits and ads. Good for most everyday use cases, but rate limits tighten during peak hours.
Claude Free provides Claude Sonnet with a daily cap. Excellent for writing, analysis, reasoning, and anything where careful, nuanced responses matter.
Gemini Free offers Gemini 3 Pro with Google Workspace integration. Probably the most capable free chat experience available if you live in the Google ecosystem.
Microsoft Copilot includes GPT-5.2 access plus free DALL-E image generation built in, which makes it uniquely useful for creative tasks.
Perplexity Free focuses on search-augmented answers with source citations. Limited daily queries but very good for research tasks where you want verifiable information.
None of these give you an API key. They are for human use, not programmatic access. For building applications, the providers in Tiers 1 and 2 are what you need.
Which Provider Should You Pick
The right answer depends entirely on what you are building. Here is a quick decision guide.
Building an app or prototype and want the most capable free option: Start with Google AI Studio. The combination of Gemini 2.5 Pro, the 1 million token context window, and no card requirement makes it the default recommendation for most developers.
Need fast responses for something user-facing: Try Groq first. If Groq's model selection does not fit, check Cerebras. Both deliver speeds that feel qualitatively different from standard providers.
Want to test multiple models or compare outputs: OpenRouter is the right tool. One key, dozens of models, free variants clearly labeled.
Building a coding assistant or working heavily on code: GitHub Models for quick evaluation, or Google AI Studio paired with OpenCode for a full free workflow. Mistral's Codestral is worth testing specifically for code-focused tasks.
Building a document search or Q&A tool: Cohere is the strongest option. Generation, embeddings, and reranking from one provider on one free tier.
Want access to the most models including specialized domain models: HuggingFace for the breadth, NVIDIA NIM for frontier model access.
Your First Free API Call in 30 Seconds
Here is working Python code for Google AI Studio. Copy it, paste in your API key, and run it.
import requests
import json
API_KEY = "your-api-key-here" # Get one free at ai.google.dev
URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key={API_KEY}"
response = requests.post(URL, json={
"contents": [{"parts": [{"text": "Explain how APIs work in two sentences."}]}]
})
print(json.loads(response.text)["candidates"][0]["content"]["parts"][0]["text"])
And here is the same thing using OpenRouter, with the standard OpenAI-compatible format:
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="your-openrouter-key", # Get one free at openrouter.ai
)
response = client.chat.completions.create(
model="meta-llama/llama-3.3-70b-instruct:free",
messages=[{"role": "user", "content": "Explain how APIs work in two sentences."}],
)
print(response.choices[0].message.content)
Both of these run completely free. No billing setup, no countdown timer.
Tips for Making the Most of Free Limits
Getting the most out of free tiers comes down to a few habits that are easy to build.
Cache your responses during development. If you are testing the same prompt repeatedly to tweak something, save the first response to a file and read from that file on subsequent runs. You save API calls without losing any testing value.
Use smaller models for iteration. During the stage where you are figuring out prompts and testing logic, run on the 8B or small model variant. Switch to the 70B or large model only when you are evaluating final quality. You can often do ten times as much iteration this way.
Spread across providers. Nothing stops you from signing up for all of them. Use Google AI Studio as your primary, Groq for speed-sensitive calls, OpenRouter when you want to compare, and DeepSeek when you need volume at near-zero cost. Managing multiple keys is a small overhead for meaningfully larger total quota.
Watch your dashboards. Every provider on this list has a usage dashboard. Checking it occasionally prevents surprises and helps you understand which parts of your code are most API-heavy.
Batch requests where possible. If you need to process 50 documents, think about whether you can send them in batches rather than 50 individual calls. Some providers count requests by API call, so fewer calls with more content per call can go further.
The Bigger Picture
The free AI inference landscape in 2026 is more capable than most people realize. You can build, test, and in many cases soft-launch AI applications without spending anything.
This was not true two years ago. The shift happened because compute costs have dropped, open-source models have caught up to proprietary ones in many tasks, and providers are competing for developer attention by making their free tiers more generous.
It will not stay this way forever. Some of these tiers will get tighter as providers optimize their economics. But right now, the window is genuinely open.
If there is a project you have been sitting on because you thought AI APIs were too expensive to experiment with, the list above is your answer. Pick one, sign up, run the example code, and see what you can build.
The only thing standing between you and a working AI-powered app at this point is an hour of your time.
Limits and availability verified as of early 2026. API tiers change frequently. Always check the provider's official documentation for current quotas before building production systems around specific limits.
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