Together AI is a cloud platform that provides developers and AI researchers with access to high-performance GPU clusters and tools for building, training, fine-tuning, and running open-source generative AI models. It offers both serverless and dedicated endpoints for inference and training.

Who is Together AI for?

Together AI is ideal for developers, AI researchers, and companies with dedicated AI/ML teams who need raw GPU power and flexibility to build custom AI applications. It is not designed for non-technical business teams seeking ready-to-use solutions.

What models are available on Together AI?

Together AI hosts over 200 open-source models, including popular ones like Meta's Llama, DeepSeek, Mixtral, and more. Models cover chat, image, vision, audio, code, language, moderation, embedding, and rerank tasks.

How do I access the models?

You can access models via Together AI’s OpenAI-compatible API. You’ll need a valid API key to make requests.

Can I use batched or parallel inference requests?

Yes, Together AI supports batching and high-concurrency usage. You can send parallel requests from your client.

Does Together AI support streaming responses?

Yes, you can receive streamed tokens by setting "stream": true in your API request.

Does Together AI support function calling or tool use?

Function calling is natively supported for some models. For others, structured prompting can simulate function-like behavior.

Can I fine-tune models on Together AI?

Yes, you can fine-tune open-source models with your own data to create task-specific models. Fine-tuning jobs are supported for various model sizes.

What factors affect fine-tuning job run time?

Run time depends on model size, training data size, and network conditions when downloading/uploading model and training files.

Can I bring my own model?

Yes, you can upload your own model weights and serve them via Together AI’s API.

What kind of GPU clusters does Together AI offer?

Together AI offers instant access to high-performance clusters, including NVIDIA H100 and B200 GPUs, with attached storage for training or large batch jobs.

Is Together AI suitable for high-throughput workloads?

Yes, Together AI supports production-scale inference. For high-throughput applications (e.g., over 100 requests per second), contact the Together AI team for dedicated support and infrastructure.

Can I deploy on specific hardware?

Yes, you can deploy on hardware of your choice, such as NVIDIA GB200 NVL72 and GB300 NVL72.

What support options are available?

Together AI offers several support tiers: Standard, which is for Scale tier API users with support during business hours; Silver, which is for Enterprise API customers with industry-leading SLAs and Slack communication; and Gold, which is for GPU Cluster customers and annual commitments with enhanced SLAs and local business hour support.

How is Together AI priced?

Pricing is based on usage (tokens for serverless endpoints) or GPU hours (for dedicated endpoints). Enterprise and cluster customers have custom pricing.

Where are the data centers located?

Together AI hosts models in secure, private data centers, including North America-based locations for certain models like DeepSeek.

Together AI ensures privacy and does not share user requests or API calls with third parties.

Together AI

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Together AI is a cloud platform that helps developers and AI researchers run, train, and fine-tune open-source AI models. It offers access to powerful NVIDIA GPUs and a wide selection of models, allowing you to build and deploy your AI applications quickly and affordably with flexible options.

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Overview Features Use Cases FAQ Integrations Pricing

About Together AI

Who It's For

This platform helps developers, AI researchers, and companies with AI teams. It's great for those needing powerful GPUs and flexible tools to build custom AI applications. It is not for non-technical users looking for ready-to-use AI.

What You Get

You access powerful NVIDIA GPUs and a library of over 200 open-source AI models for tasks like chat or images. The platform offers tools to run models, fine-tune them with your data, or train new ones. You also get flexible options, from serverless to dedicated hardware.

How It Works

You connect via an easy API. Select models, customize them with your data using fine-tuning, or run them to power your apps. The system is designed for speed and cost-effectiveness, helping you deploy AI projects quickly and affordably.

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Features & Capabilities

⚙️ Core AI Platform Services

Serverless Inference API

Deploy and run inference on open-source AI models without managing underlying servers.

Fine-Tuning Platform

Train and improve high-quality, task-specific models using your proprietary data.

Model Library

Explore and build with a diverse collection of open-source and specialized AI models.

Pre-Training Capabilities

Securely and cost-effectively train custom AI models from the ground up.

⚡ High-Performance GPU Infrastructure

Instant GPU Clusters

Access self-service NVIDIA GPUs instantly for rapid model deployment and training.

Dedicated Endpoints

Deploy models on custom hardware with guaranteed capacity and expert support.

Global Data Center Network

Leverage GPU power distributed across 25+ data center locations worldwide.

Frontier Hardware Support

Utilize cutting-edge NVIDIA GPUs like GB200 NVL72 for optimal performance.

🛠️ AI Development & Agentic Tools

Code Sandbox

Create secure and isolated development environments for building AI applications.

Code Interpreter

Safely execute LLM-generated code to enhance AI agent capabilities.

LLM Selection Tool

Find the most suitable large language model for your specific application requirements.

Advanced Tool Calling

Integrate external tools and functions into AI agents for complex use cases.

📊 Performance & Cost Optimization

ATLAS Inference System

Accelerate LLM inference by up to 4x using runtime-learning techniques.

Batch Inference API

Process billions of tokens at a 50% lower cost for efficient large-scale inference.

Optimized Unit Economics

Achieve industry-leading performance-to-cost ratios for AI workloads.

Production Scale Reliability

Ensures stable and consistent performance for high-volume, production-grade applications.

Use Cases

Accelerating Production AI Inference at Scale

Organizations face challenges deploying generative AI models with high performance and cost-efficiency in production. Together AI's serverless and dedicated inference endpoints, powered by innovations like ATLAS, deliver unmatched price-performance, enabling reliable deployment of open-source models for high-throughput and streaming applications.

B2B SaaSFor: AI/ML Engineers

Customizing and Deploying Task-Specific LLMs

Generic open-source models often lack the specificity required for unique business challenges. Together AI's fine-tuning platform allows developers to train models with proprietary data, creating highly accurate, task-specific, and cost-effective AI solutions that are fully owned and easily integrated into production workflows.

Any Industry leveraging Specialized AIFor: Machine Learning Engineers

Building and Executing AI Agents with Code Capabilities

Developers creating sophisticated AI agents need robust environments for code generation and execution. Together AI's Code Sandbox and Code Interpreter, combined with high-performance GPU clusters and support for advanced tool calling, provide the necessary infrastructure to rapidly build, test, and scale AI-native applications.

Software DevelopmentFor: AI Developers

Provisioning Enterprise-Grade GPU Infrastructure for AI Workloads

Large enterprises require secure, reliable, and massively scalable GPU clusters for pre-training custom models and deploying complex AI solutions globally. Together AI offers "Frontier AI Factory" and Reserved Clusters with NVIDIA's latest hardware across global data centers, providing the dedicated capacity and expert support needed for critical enterprise AI initiatives.

Large EnterpriseFor: Enterprise Architects

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