Together AI is an AI infrastructure platform for model APIs, inference, fine-tuning, dedicated endpoints, GPU clusters, and production deployment.

How is Together AI priced?

Together AI uses usage-based pricing across tokens, media generation, GPU hours, fine-tuning, storage, code sessions, and dedicated capacity.

Who should use Together AI?

It is best for developers, AI startups, and engineering teams building products on open models or scalable AI infrastructure.

Does Together AI support image and video models?

Yes. Together AI lists pricing for text, image, video, audio, embeddings, reranking, and other model categories.

Can Together AI provide dedicated endpoints?

Yes. Together AI supports dedicated inference, provisioned throughput, GPU clusters, and reserved capacity options.

What should buyers watch for?

Teams should monitor token volume, model selection, GPU hours, storage, code sessions, reserved capacity, and traffic spikes.

Together AI

Name: Together AI
Brand: Together AI

AI infrastructure platform for model APIs, inference, fine-tuning, and GPUs.

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What is Together AI?

TL;DR

Together AI is an AI infrastructure platform for running, fine-tuning, evaluating, and deploying open and proprietary models through APIs, serverless inference, dedicated compute, and developer tools.

Serverless inference across many text and media models
Dedicated endpoints, provisioned throughput, and GPU clusters
Fine-tuning, embeddings, reranking, code sessions, and storage

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About

Together AI is a developer platform for running open-source and commercial AI models through APIs, serverless inference, dedicated endpoints, GPU clusters, fine-tuning, code execution, storage, and production infrastructure. It gives teams access to many model families without operating the full serving stack themselves. The product is useful for developers, AI startups, and engineering teams building applications on open models. Together AI supports text, image, audio, video, embeddings, reranking, dedicated inference, provisioned throughput, fine-tuning, GPU clusters, code interpreter sessions, and file-system storage. Together AI pricing is usage-based rather than a simple subscription. Costs vary by model, input tokens, output tokens, media generation, GPU hour, storage, code sessions, fine-tuning, and reserved capacity. That makes it powerful for production builders, but cost monitoring is essential. For FutureStack, Together AI belongs in Developer Tools because it is infrastructure for AI products. It is best for teams that need model APIs, open-model inference, dedicated endpoints, fine-tuning, GPU capacity, and scalable AI deployment options.

Use Cases

Model Inference

Run supported AI models through APIs and hosted infrastructure for applications and production workloads.

Model Fine-tuning

Customize supported open models for domain-specific behavior and application requirements.

AI Application Hosting

Use serverless or dedicated compute options to deploy model-powered applications and services.

Model Evaluation

Test and compare models and configurations before choosing an approach for production AI systems.

Key Features

Serverless inference across many text and media models
Dedicated endpoints, provisioned throughput, and GPU clusters
Fine-tuning, embeddings, reranking, code sessions, and storage
Usage-based pricing across tokens, GPUs, media, and infrastructure

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