Where to look
For most people, the models page is enough. Use it to:- browse the full catalog
- compare providers and pricing
- see which models support tools, multimodal input, reasoning, or other capabilities
- find free models
- copy the exact model ID you want to use
Free and paid models
NagaAI has both free and paid models. Free models are marked with the:free suffix. They are good for testing, experimenting, and lighter workloads.
Paid models require a positive account balance. They give you access to the broader catalog and are the usual choice for production work.
If your goal is simply “find a free model I can try right now”, the quickest path is to open naga.ac/models and filter for :free.
How to think about model choice
The first question usually is not “which provider do I want?” It is “what am I building?” If you are building chat, assistants, or agent-style workflows, you will usually be looking at models you can use with Responses API. If you are building retrieval or RAG, you need an embeddings model. If you are working with transcription, translation, or text-to-speech, you need an audio model. If you need safety checks, you need a moderation model. If you want to generate or edit images, you need an image model.LLM Apps
Use
Responses API for chat, assistants, tools, and multimodal workflows.Embeddings
Use an embeddings model for retrieval, ranking, semantic search, and RAG.
Audio
Use audio models for speech-to-text, translation, and text-to-speech.
Moderation
Use moderation models when you need text or image safety checks.
Images
Use image models when you need image generation or image edits.
What matters when choosing
When you compare models on NagaAI, the things that usually matter are:- whether the model is free or paid
- whether it supports the capability you need
- how much it costs
- whether it is a good fit for experimentation or production
If you need the catalog in code
The website is the best place to explore models as a human./v1/models exists for the cases where you want the live catalog programmatically, for example in scripts, internal dashboards, or dynamic model selectors.