Together AI
By Together AI
Together AI is a cloud platform that provides API access to open-source large language models for inference and fine-tuning, along with GPU cloud infrastructure for training AI models at scale.
Definition
Together AI is a cloud platform that provides API access to open-source large language models for inference and fine-tuning, along with GPU cloud infrastructure for training AI models at scale.
Overview
Together AI focuses on making open-source models — such as Llama, Mixtral, and other community-released LLMs — as easy to use as proprietary APIs like OpenAI's. Developers call hosted models through a standard API for chat, completion, embeddings, and image generation, without needing to provision or manage GPU servers themselves. Beyond hosted inference, Together AI offers fine-tuning services so teams can customize open-source models on their own data, and dedicated GPU cloud infrastructure for larger training and inference workloads that need more control than a shared API endpoint. This combination of managed inference plus raw compute access positions it between fully managed model APIs and infrastructure-only providers like RunPod. Because it specializes in optimizing inference speed and cost for open large language models, Together AI is often compared with other open-model inference platforms such as Groq and Fireworks AI, with competition centered on latency, throughput, pricing, and the breadth of supported models.
Key Features
- Hosted API access to a wide range of open-source large language models
- Fine-tuning services for customizing open models on proprietary data
- Dedicated GPU cloud instances for training and large-scale inference
- Optimized inference infrastructure for lower latency and cost
- Support for embeddings, chat, and image-generation model endpoints
- Compatibility with common API formats used by other LLM providers
- Usage-based pricing without requiring long-term infrastructure commitments
Use Cases
Frequently Asked Questions
From the Blog
Embeddings Explained: How AI Understands Meaning
Embeddings turn words, sentences, and images into vectors of numbers so that similar meanings sit close together, letting AI compare and search by meaning.
Read More AI & TechnologyHow to Evaluate LLMs: Benchmarks and Metrics
Evaluating a language model means measuring how well it does the job you need, using benchmarks, task-specific metrics, and human or model-based judgment together.
Read More AI & TechnologyWhat Is an Epoch, Batch and Iteration in Training
An epoch is one full pass over your training data, a batch is a slice of it, and an iteration is one weight update. Here is how the three fit together.
Read More AI & TechnologyVerbal vs Non-Verbal Communication: What's the Difference?
Verbal communication uses spoken or written words, while non-verbal communication conveys meaning through tone, body language, and expression — the two usually work together. This guide explains both and how to strengthen them.
Read More