Summarize this article with:
A free LLM API gives developers API-based access to a large language model without paying for initial usage. Groq, OpenRouter, and Eden AI are three of the strongest options to test first:
- Eden AI includes free Gemma 4 models with a 262K-token context window in the EU region, a combination of free access, long context, and EU data residency not matched by the other free tiers compared here.
- Groq provides model-specific free rate limits, while OpenRouter exposes a rotating catalog of free model variants.
- Google, Cerebras, Cloudflare, NVIDIA, Hugging Face, Mistral, and GitHub also provide free LLM API resources with different restrictions.
Best Free LLM APIs in 2026 Comparison Table
What counts as a "free" LLM API?
A free LLM API gives you hosted access to a language model through an API without paying for at least a defined amount of ongoing usage. That is different from a temporary trial or downloading model weights to run yourself.
There are three categories worth separating:
- Free tier. This is the most useful option for developers who want to keep testing without paying. The provider gives you a recurring free quota, usually with limits on requests per minute, requests per day, or tokens. A true free tier does not require you to buy credits just to start using the API. Some providers also let you create a free LLM API key without adding a credit card.
- Free trial credits. These are temporary. You receive a fixed balance when you sign up, and usage becomes paid once the credits expire or run out. Trials may also require a payment method before activation. They are useful for evaluation, but they should not be treated as a permanent free API tier.
- Open weights you host yourself. Models such as Llama, Gemma, or Mistral releases may be available to download under their respective licenses, but running them still requires compute. You pay for GPUs, cloud instances, electricity, orchestration, and maintenance.
Option 3 is not a free API. The model weights may cost nothing to download, but there is no hosted API quota included. That distinction matters because developers searching for free LLM APIs usually want an endpoint they can call immediately, not an infrastructure project they have to operate themselves.
The 11 best free LLM API providers in 2026
1. Eden AI
Free quota: Free models; current provider-specific limits are listed in the Eden AI model catalog.
Models: google/gemma-4-26b-a4b-it, google/gemma-4-31b-it, plus selected Cloudflare-hosted Gemma, Llama, and Mistral models.
Context: Up to 262K tokens on the Google-hosted Gemma 4 models.
Card required: See model catalog.
Commercial use: See model catalog and underlying model/provider terms.
Best for: Free EU-hosted LLM access and developers who may later need paid models through the same gateway.
Watch out for: Free-model limits and conditions depend on the upstream host, so Google-hosted and Cloudflare-hosted models do not necessarily have the same quotas or terms.
The standout free options are Eden AI's Gemma 4 models with 262K context and EU-region hosting. The free models are ultimately hosted by their upstream providers - currently Google or Cloudflare - so the Eden AI model catalog should remain the source of truth for availability and model-specific conditions.
The Cloudflare-routed models are generally smaller and older. They can make sense for lightweight classification, extraction, rewriting, or simple drafting, but they should not be treated as substitutes for current frontier reasoning models.
The useful architectural point is that Eden AI exposes free and paid models through the same platform. If a prototype later needs Claude, GPT, Gemini, or another provider, the application can generally switch the model selection rather than migrate to a completely different provider account and SDK.
2. Google AI Studio (Gemini)
Free quota: Model-specific; free-tier RPM and RPD vary by Gemini model.
Models: Gemini Flash, Flash-Lite, and selected other Gemini models.
Context: Up to 1M+ tokens, depending on the model.
Card required: No for the standard AI Studio free API-key flow.
Commercial use: Yes, subject to Gemini API terms.
Best for: Multimodal prototypes and applications that need very large context windows.
Watch out for: Content submitted through the Gemini API Free Tier may be used by Google to improve its products.
Google AI Studio is one of the strongest free options if context length and multimodal input matter more than predictable throughput. Google provides free-tier access to eligible Gemini models, particularly in the Flash and Flash-Lite families, while limits vary by model and can change.
That volatility is why it is safer to check the active limits in AI Studio rather than build capacity assumptions around a copied RPM figure. The free tier also has an important privacy trade-off: Google's current pricing documentation marks free-tier content as being used to improve its products, while paid-tier content is marked differently.
Gemini also provides an official OpenAI compatibility layer. Existing Python applications using the OpenAI client can point to Google's compatibility endpoint and change the model name, although not every Google-specific feature maps perfectly to OpenAI's API.
3. Groq
Free quota: Model-specific; for example, llama-3.1-8b-instant currently has 30 RPM, 14,400 RPD, 6K TPM, and 500K TPD.
Models: Llama, GPT-OSS, Qwen, Groq Compound, and others.
Context: Up to 131,072 tokens on several current production models.
Card required: No.
Commercial use: Depends on the underlying model license and Groq terms.
Best for: Very fast text generation, agents, and latency-sensitive prototypes.
Watch out for: Rate limits are enforced at the organization level, so creating additional API keys does not multiply your quota.
Groq is attractive when the bottleneck is inference latency rather than access to the largest possible catalog. Its free plan exposes several production models with model-specific RPM, RPD, TPM, and daily-token caps. llama-3.1-8b-instant, for example, has a much higher daily request allowance than some of Groq's larger models.
This means "Groq's free limit" is not one number. Always check the model you actually plan to call. A workload can also hit its token limit before its request limit, especially with long prompts.
Groq's API is mostly OpenAI-compatible, so integration is straightforward. There are still parameter differences: some OpenAI fields are unsupported or behave differently, which matters when migrating an existing agent or structured-output workflow.
4. OpenRouter
Free quota: 20 RPM / 50 requests per day, or 1,000 requests per day after at least $10 in credits has been purchased historically.
Models: 20+ rotating free-model variants across multiple model developers.
Context: Model-dependent; some free models offer very large context windows.
Card required: No for basic free-model access.
Commercial use: Depends on the selected model and upstream license.
Best for: Comparing many models behind one OpenAI-style API.
Watch out for: The free model catalog rotates, and free upstream capacity can disappear temporarily.
OpenRouter gives developers one of the broadest free catalogs without requiring a separate API integration for every model developer. Free variants use the :free suffix, and OpenRouter also provides an openrouter/free router that automatically selects an available free model.
The free quota is account-wide rather than per model. Accounts that have purchased less than $10 in credits receive 20 RPM and 50 free-model requests per day. Once at least $10 has been purchased over the lifetime of the account, the daily allowance rises to 1,000 while RPM remains 20. Additional keys do not bypass the account-level limits.
The trade-off is predictability. Free capacity comes from upstream providers, so models can become unavailable or congested. Pin a specific :free model when model consistency matters; use the free router when availability matters more than knowing exactly which model handles each request.
5. Cerebras
Free quota: Model-specific; some free-plan models allow up to roughly 1M tokens per day.
Models: GPT-OSS and other selected models available in Cerebras Inference.
Context: Model-specific, with large-context options available.
Card required: No.
Commercial use: Depends on the model and Cerebras terms.
Best for: Developers testing extremely fast inference on reasoning and coding workloads.
Watch out for: Free-plan rate limits vary substantially by model, so a headline daily token allowance does not describe the full constraint.
Cerebras differentiates itself primarily on inference speed. The hosted API can be used with a free account, but quotas should be checked model by model because request-per-minute, token-per-minute, and token-per-day limits can all apply simultaneously.
For a real application, the token-per-minute ceiling may matter more than the nominal daily allowance. A long-context coding or reasoning workload can exhaust throughput with only a small number of requests.
Cerebras exposes an OpenAI-compatible API at https://api.cerebras.ai/v1, making it easy to test in an existing OpenAI-based application. There are implementation differences, though. For example, support for combining tools with structured response formats can vary by model, and some Cerebras-specific parameters need to be passed through extra_body.
That makes Cerebras particularly compelling for benchmarks where latency is the variable you want to test, but you should validate agent behavior rather than assuming complete OpenAI feature parity.
6. Cloudflare Workers AI
Free quota: 10,000 Neurons per day.
Models: 20+ LLMs plus embedding, vision, speech, and other AI models.
Context: Model-dependent.
Card required: No for the standard free allocation; some individual models require paid billing.
Commercial use: Model-dependent.
Best for: Developers already building on Cloudflare Workers and edge infrastructure.
Watch out for: The 10,000-Neuron daily budget is shared across Workers AI usage, and different models consume Neurons at different rates.
Cloudflare does not meter its free AI tier primarily in requests or tokens. Instead, Workers AI provides 10,000 Neurons per day, with Neurons representing the compute used by a request. The allowance resets daily, but the number of prompts it buys depends heavily on the chosen model, input size, and output size.
That makes direct comparisons with a "1,000 requests/day" provider misleading. A small model and a larger reasoning model can consume very different portions of the same free budget.
Cloudflare now provides OpenAI-compatible endpoints for text generation and embeddings. The base URL includes your Cloudflare account ID, so this integration requires both an API token and account identifier.
Workers AI is particularly convenient when inference is already part of a Cloudflare application. Be aware that certain newer frontier models explicitly require a paid billing method even though Workers AI itself includes the daily free allocation.
7. NVIDIA NIM
Free quota: Free NVIDIA-hosted endpoints for development, testing, research, and prototyping; exact hosted limits are model-specific.
Models: Nemotron, Llama, GPT-OSS, DeepSeek, Mistral, Qwen, and others.
Context: Model-specific; several models support large context windows.
Card required: No for Developer Program prototyping access.
Commercial use: No for free production use; NVIDIA AI Enterprise is required for production.
Best for: Evaluating NVIDIA-optimized inference before deploying NIM in enterprise infrastructure.
Watch out for: NVIDIA explicitly defines serving real end-users or conducting business transactions as production, not prototyping.
NVIDIA's free access is best understood as an evaluation and development program rather than a permanent free production API. Members of the NVIDIA Developer Program can use NVIDIA-hosted API endpoints for prototyping and access downloadable NIM microservices for research, development, and testing.
Once the application moves into production, NVIDIA says an NVIDIA AI Enterprise license is required. Its documentation explicitly includes real end-user activity and business transactions in the definition of production use.
The model catalog is broad and includes both NVIDIA models and third-party families. NVIDIA's LLM API follows the familiar chat-completions structure, making it relatively easy to test with an OpenAI client. The hosted inference endpoint currently uses integrate.api.nvidia.com.
8. Hugging Face Inference
Free quota: $0.10 in monthly Inference Providers credits for free users, subject to change.
Models: Hundreds of models routed through multiple inference providers.
Context: Model-dependent.
Card required: No to use the included monthly credits; additional usage requires purchased credits.
Commercial use: Model- and provider-dependent.
Best for: Exploring many open and hosted models through one account.
Watch out for: Hugging Face's free allowance is a small monthly credit balance, not a fixed number of free requests.
Hugging Face Inference Providers has changed significantly from the older "serverless Inference API" many articles still describe. Current free users receive $0.10 in monthly credits, which Hugging Face notes is subject to change. The number of requests this represents depends on the selected model and inference provider.
Inference Providers acts as a router across external inference services, letting developers access hundreds of models without setting up a separate provider account for each one. You can also bring a custom provider key, although Hugging Face's monthly credits do not apply in that mode.
For text chat, Hugging Face exposes an OpenAI-compatible endpoint at https://router.huggingface.co/v1. The same compatibility does not automatically extend to every modality; for example, Hugging Face explicitly notes that its OpenAI-compatible client is not the route for image generation.
9. Mistral La Plateforme
Free quota: Free mode with included monthly API usage; exact current limits are shown in the Mistral Admin Panel.
Models: Mistral's current hosted model catalog.
Context: Model-dependent, including long-context models.
Card required: No.
Commercial use: Yes.
Best for: Testing Mistral models directly through the company's own API.
Watch out for: Mistral no longer exposes one stable public free-tier quota; the actual limits for your organization are shown in Admin Panel → API → Limits.
Mistral's free offering is called Free mode. It lets users create API keys and consume the included monthly usage, but the company now directs developers to the Admin Panel for the current rate limits rather than maintaining one universal public RPM or monthly-token figure.
That is important because older comparisons commonly quote an "approximately 1B tokens/month" allowance. Unless that figure appears in the active account limits at publication time, it should not be treated as a guaranteed current quota.
Rate limits are shared at the Workspace level across API keys. Creating several keys inside the same Workspace therefore does not create independent throughput pools.
Mistral's Chat Completions API follows the OpenAI request structure, and the company documents https://api.mistral.ai/v1 as the compatible base URL.
10. GitHub Models
Free quota: For Copilot Free, Low-tier models: 15 RPM / 150 RPD; High-tier models: 10 RPM / 50 RPD.
Models: Models from OpenAI, Microsoft, Meta, DeepSeek, and other publishers; catalog changes over time.
Context: Free API requests are subject to per-request token limits defined by rate-limit tier.
Card required: No for free experimentation.
Commercial use: Free limits are intended primarily for experimentation; production usage moves to paid access.
Best for: Developers already using GitHub who want to compare models quickly.
Watch out for: Limits depend on whether GitHub classifies a model as Low, High, or Embedding, so there is no single GitHub Models quota.
GitHub Models provides a playground and API specifically designed to let developers experiment with multiple AI models. GitHub's official documentation currently gives Copilot Free users 15 RPM and 150 RPD for Low-tier models, while High-tier models receive 10 RPM and 50 RPD. Token limits per request also differ by tier.
Those free limits are explicitly positioned for experimentation. GitHub recommends moving beyond the free offering when an application is ready for production.
The current REST inference endpoint is https://models.github.ai/inference/chat/completions, and requests authenticate with a GitHub token that has model-read permission.
Because the available publishers and model tiers can change, check the Marketplace model card before assuming that a model inherits the Low-tier limits shown above.
11. Together AI
Free quota: None currently. Together AI no longer offers a free trial.
Models: Broad catalog of hosted open and third-party models.
Context: Model-specific.
Card required: Yes - a minimum $5 credit purchase is required for platform access.
Commercial use: Model-dependent.
Best for: Paid serverless inference across a wide selection of models, not developers specifically seeking a free API.
Watch out for: Many older "free LLM API" lists still describe Together AI as offering signup credits, but that information is now outdated.
Together AI remains in this comparison because it frequently appears in older lists of free LLM API providers. As of the current documentation, however, Together AI does not offer a free trial. New platform access requires purchasing at least $5 in credits, and the account must maintain a positive balance to continue making API calls.
That means Together AI no longer meets the definition of a free tier used in this article. Developers specifically looking to start without paying should choose one of the providers above instead.
Together is still technically easy to migrate to later. Its inference API is OpenAI-compatible across chat and several other capabilities, with https://api.together.ai/v1 as the standard base URL.
The broader lesson is why free-API comparisons need dates: a provider can move from free signup credits to prepaid-only access while outdated articles continue ranking for years.
How to get a free LLM API key with Eden AI
Here’s how to generate a free LLM API key with Eden AI in just a few minutes. You can create an account, generate your API key from the dashboard, and start testing the free LLM models available in the Eden AI catalog.
- Create an Eden AI account at https://app.edenai.run/playground.
- Open API Keys at https://app.edenai.run/settings/api-keys.
- Create an API key, then select one of the free models from the current Eden AI model catalog. Check the catalog for current model-specific account requirements and availability.
Which free LLM API should you choose?
Free open-weight LLMs in 2026 you can self-host
A common mistake is to use "open weights" and "open source" as if they mean the same thing. They do not. Under the Open Source AI Definition, an open-source AI system should provide the information and components needed to study, modify, and reproduce it, including training code, sufficiently detailed training-data information, and model parameters under appropriate open terms.
An open-weight model is a narrower category: you can download and run the trained weights, but the organization may not publish the full training dataset or training pipeline, and the weights may come with a custom license or usage restrictions. Meta's Llama and Google's Gemma families are good examples of why developers should read the actual model license instead of assuming that downloadable weights mean unrestricted open source. Google's Gemma models, for example, are governed by dedicated Gemma terms rather than a standard OSI software license.
Here are the current model families worth considering for self-hosting:
Self-hosting gives you more control over infrastructure, data location, quantization, and fine-tuning, but it is not a free LLM API. Downloading the weights may cost nothing, while serving them still requires CPU or GPU capacity, storage, networking, monitoring, and engineering time. Larger models may need multiple high-memory accelerators or aggressive quantization before they are practical to run.
That makes open weights attractive when control or predictable infrastructure matters more than zero-cost experimentation. If your goal is simply to obtain an endpoint and start sending requests, one of the hosted free tiers above is usually much easier.
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