46 AI Models You Can Use for Free via NVIDIA NIM in 2026

NVIDIA hosts 46 AI models from 12 publishers with free API access. No credit card, no trial timer. Here is every model worth using and how to get started in five minutes.

• NVIDIA has built one of the most useful free resources in AI. Their NIM platform at build.nvidia.com hosts 46 AI models from 12 different publishers — and you can use all of them through a standard API at no cost. No credit card. No trial timer. No catch other than rate limits.
• These are not demo models or watered-down versions. The free list includes MiniMax M2.7 (a 230 billion parameter model that competes with Claude on coding tasks), Qwen3 Coder 480B (purpose-built for agentic coding), Mistral Large 3 675B (a state-of-the-art general purpose model), and Meta's Llama 4 Maverick (the most popular model on the platform with 22 million uses).
• This guide covers what is available as of May 2026, which models are worth your time for different use cases, and how to start using them in under five minutes.

How NVIDIA NIM Actually Works

NVIDIA NIM stands for NVIDIA Inference Microservices. It is a platform where NVIDIA hosts AI models on their own DGX Cloud hardware and exposes them through a standard API that is compatible with the OpenAI format.

This compatibility is the key feature. Any code, tool, or framework that works with the OpenAI API also works with NVIDIA NIM. You change two things: the base URL (to https://integrate.api.nvidia.com/v1) and the API key (to your nvapi key). Everything else — your code, your prompts, your tool configurations — stays exactly the same.

You get free inference credits on signup with a rate limit of approximately 40 requests per minute. Larger models consume more compute per request, but for text-based coding and chat models, you can run hundreds of conversations before hitting any meaningful limit.

NVIDIA is not doing this purely out of generosity. The free tier is a top-of-funnel strategy for NVIDIA AI Enterprise, their paid inference and deployment platform. The path is: prototype free on NIM, test on GPU sandbox hardware, then deploy with a paid enterprise licence. But the free tier itself is genuinely useful and there is no obligation to upgrade.

Source: NVIDIA NIM documentation, build.nvidia.com, May 2026.

The Best Free Models by Use Case

Not all 46 free models are equally useful for every task. Here are the ones worth trying, organised by what they do best. All usage numbers are from build.nvidia.com as of May 13, 2026.

For coding and software development, MiniMax M2.7 is the strongest all-round option. It is a 230 billion parameter sparse Mixture of Experts model with 11.3 million uses on the platform. It handles code generation, debugging, refactoring, and code review at a level that competes with paid models from major providers. Qwen3 Coder 480B is purpose-built for agentic coding with a 256,000 token context window and 4.5 million uses. If you are using tools like Aider or Cline that rely on function calling, Mistral Nemotron is the best choice — it was specifically built for agentic workflows, instruction following, and function calling.

For general reasoning and chat, Llama 4 Maverick from Meta is the most popular model on the platform with 22 million uses. It is multimodal (handles both text and images) and works well for general-purpose tasks. Mistral Large 3 675B is another strong option for complex reasoning and professional writing. Step-3.5 Flash from Stepfun is a 200 billion parameter reasoning engine designed for agentic AI with 11.2 million uses.

For edge and mobile applications, Google's Gemma 3n models (E2B and E4B) are designed specifically for resource-constrained environments. They accept text, audio, and image input. Microsoft's Phi-4 Multimodal handles image and audio reasoning in a compact form factor.

For specialised tasks, NVIDIA hosts its own models for text embeddings (NV-Embed V1), code embeddings (NV-EmbedCode 7B), content safety moderation (Nemotron Content Safety), translation (Riva Translate in 12 languages), text-to-speech (Magpie TTS), and even protein structure prediction (ESMFold) and autonomous driving perception (StreamPETR, BEVFormer).

NVIDIA Models vs Third-Party Models

An important distinction that most guides miss: NVIDIA NIM hosts two types of models on its free tier.

NVIDIA's own models are built and trained by NVIDIA. On the free tier, these are primarily specialised models: Nemotron Mini 4B (optimised for on-device inference and roleplay), Nemotron Content Safety (for moderation), NV-Embed V1 (for text embeddings), NV-EmbedCode 7B (for code search), Riva Translate (12-language translation), and several autonomous driving and video analysis models. NVIDIA's flagship Nemotron 3 Super 120B is not on the free tier — it is available through paid partner endpoints from Bitdeer, CoreWeave, and DigitalOcean.

Third-party models are built by other companies but hosted on NVIDIA's infrastructure for free. These include the models most developers actually want: MiniMax M2.7, Qwen3 Coder 480B, Mistral Nemotron, Mistral Large 3 675B, Meta's Llama 4 Maverick, Google's Gemma family, Microsoft's Phi-4, ByteDance's Seed-OSS 36B, Stepfun's Step-3.5 Flash, and others.

The third-party models on NVIDIA NIM are typically the same models available directly from each provider's own API. MiniMax M2.7 on NVIDIA NIM is the same model as MiniMax M2.7 on MiniMax's own platform. The difference is that the provider charges per token on their own platform, while NVIDIA hosts it for free with rate limits.

One caveat: the free model catalogue is not static. Models can be added, deprecated, or removed. During our research for this article, we observed several models carrying deprecation notices (Kimi K2 Instruct, Kimi K2 Thinking, GLM-4.7, Gemma 3 27B). Check build.nvidia.com/models for the current list before building a workflow around a specific model.

What Costs Money Elsewhere Is Free Here

To put the free tier in context, here is what these same models cost when accessed through their native providers or third-party hosting services.

MiniMax M2.7 is available on MiniMax's own API with per-token pricing. Mistral Large 3 675B costs money through Mistral's La Plateforme. Llama 4 Maverick is free to download and self-host, but running a 128-expert Mixture of Experts model requires expensive GPU hardware.

NVIDIA's own Nemotron models, while not on the free tier, are available through partner endpoints. Nemotron 3 Super 120B costs $0.20 per million input tokens and $0.80 per million output tokens through Bitdeer or CoreWeave. Nemotron Super 49B costs $0.10 per million input tokens through DeepInfra. These are already among the cheapest models in the market, and the free tier lets you use comparable third-party models at zero cost.

For developers using AI coding tools, the savings are significant. A typical Aider or Cline user running Claude Sonnet 4.6 spends $15 to $30 per month on API calls. Cursor Pro costs $20 per month. Claude Code with an Anthropic subscription starts at $20 per month for the basic plan. All of these costs drop to zero when you route through NVIDIA NIM's free models.

How to Get Started in Five Minutes

Step 1: Go to build.nvidia.com and create a free account. Verify your email address.

Step 2: Navigate to build.nvidia.com/settings/api-keys and generate an API key. Save it securely — you only see it once. It starts with nvapi- and is about 56 characters long.

Step 3: Test your key with a simple curl command. Open your terminal and run:

curl https://integrate.api.nvidia.com/v1/chat/completions -H "Authorization: Bearer nvapi-YOUR-KEY" -H "Content-Type: application/json" -d '{"model": "minimaxai/minimax-m2.7", "messages": [{"role": "user", "content": "Write a Python function to reverse a string"}]}'

If you get a response with generated code, your key works. If you get a 403 error, your account may need the Public API Endpoints permission — check the NVIDIA Developer Forums for instructions.

Step 4: Browse the model catalogue at build.nvidia.com/models and filter by Free Endpoint to see all 46 available models. Each model page shows example code and the exact model ID to use in API calls.

Step 5: Connect to your preferred coding tool. For AI coding assistants like Aider, Cline, or Claude Code, see our companion guide on setting up each tool with NVIDIA NIM.

Limitations You Should Know

The free tier has real constraints that matter for serious use.

Rate limits sit at approximately 40 requests per minute. This is comfortable for interactive coding but will bottleneck automated pipelines. If you hit 429 (Too Many Requests) errors, add a delay between requests or reduce your batch size.

There are no production guarantees. Response times can spike during peak hours, and there is no Service Level Agreement on the free tier. Do not build customer-facing products on this endpoint.

You cannot fine-tune models on the free tier. What NVIDIA hosts is what you get. If you need a customised model, you will need to self-host using NVIDIA NIM containers on your own GPU hardware.

Model availability changes. Free models can be deprecated or removed with a few days notice. During our research, we observed deprecation notices on several previously popular models. Build your workflow to be model-flexible — if one model gets removed, you should be able to swap in another with minimal disruption.

Despite these limitations, NVIDIA NIM is the most generous free AI API available in 2026. 46 models from 12 publishers, no credit card required, and enough rate limit for meaningful development work.

The Bottom Line

NVIDIA NIM is the best free AI API platform available in 2026. 46 models from 12 publishers, no credit card, and enough rate limit for real development work. The model quality is genuinely strong — MiniMax M2.7 and Qwen3 Coder 480B compete with paid models on coding benchmarks, and Mistral Nemotron is one of the best function-calling models available at any price.

For developers, the biggest value is using NIM to power AI coding tools for free. Aider, Cline, Continue.dev, and even Claude Code (via proxy) all work with NVIDIA NIM. That is potentially $20 to $100 per month in API costs or subscriptions eliminated.

For students and researchers, the free credits are enough to prototype with frontier-class models without any budget. For startups, it is a way to build and test AI-powered features before committing to a paid provider.

Start at build.nvidia.com, get your free API key, and explore the catalogue. We track pricing for all NVIDIA Nemotron models alongside 300 plus other AI tools at aitoolsmentor.com/models. The numbers update weekly.