Together AI

What is Together AI

Together AI is an AI Acceleration Cloud that provides an end-to-end platform for the full generative AI lifecycle. It offers fast, scalable inference, fine-tuning, and training across open-source models with OpenAI-compatible APIs. Teams can serve chat, image, and code models, customize them with their own data, and deploy reliably on high-performance GPU clusters. By unifying model serving, model customization, and large-scale training under one API and control plane, Together AI helps developers optimize performance and cost while accelerating time to production.

Together AI Main Features

• High-performance inference: Low-latency, cost-efficient serving for leading open-source models across chat, vision, and code.
• OpenAI-compatible APIs: Drop-in endpoints for chat/completions, images, and embeddings to simplify integration and migration.
• Fine-tuning at scale: Manage dataset prep, job orchestration, and checkpointing to tailor models to domain data.
• Full-stack training: Train and evaluate models on scalable GPU clusters with job monitoring and logs.
• Model catalog: Access 200+ generative AI models spanning LLMs, vision-language, and diffusion models.
• Deployment flexibility: Shared or dedicated clusters, with options for private models and enterprise controls.
• Observability: Metrics, tracing, and evaluations to track quality, throughput, and cost over time.
• Cost controls: Quotas, rate limits, and usage insights to manage spend across teams and environments.

Who Should Use Together AI

Together AI suits software teams, AI platform engineers, data scientists, and startups building production-grade generative AI. it's ideal for organizations standardizing on open-source models, needing fast inference with predictable cost, or requiring managed fine-tuning and training on scalable GPU infrastructure. Typical use cases include chat assistants, content and image generation, code completion, RAG pipelines, and domain-specific model customization.

How to Use Together AI

1. Create an account and generate an API key in the dashboard.
2. Choose a model from the catalog (e.g., chat, image, or code) that fits your task and latency/cost goals.
3. Integrate the OpenAI-compatible API in your app for chat/completions, images, or embeddings.
4. Evaluate baseline quality with small prompts or datasets; capture metrics and latency.
5. Prepare training data (instruction, preference, or domain data) and launch a fine-tuning job if customization is needed.
6. Validate the tuned checkpoint with offline evals and A/B tests; monitor cost and throughput.
7. Promote the model to production, set up observability dashboards, and configure quotas and rate limits.
8. Iterate: retrain or retune as data drifts, and scale capacity on GPU clusters as traffic grows.

Together AI Industry Examples

Ecommerce teams deploy multilingual chat agents and product search with embeddings to improve conversion. Media and design platforms run image generation and upscaling at scale for user content workflows. Financial services fine-tune LLMs on internal documents for compliant summarization and analyst copilots. Developer tooling companies serve code models for completion and test generation, combining fast inference with private fine-tuned checkpoints.

Together AI Pricing

Together AI typically uses usage-based pricing. Inference is billed per output (for example, per token or image) with rates that vary by model. Fine-tuning and training are billed based on compute and storage consumed, with options for dedicated capacity. Volume discounts and enterprise agreements are available for larger workloads. Refer to the official pricing page for current model rates and any available trial credits.

Together AI Pros and Cons

Together AI FAQs

• Does Together AI support open-source models?

  Yes. It focuses on serving and customizing leading open-source models across text, vision, and code.

• Are the APIs compatible with OpenAI SDKs?

  Together AI provides OpenAI-compatible endpoints, so many clients and SDKs work with minimal changes.

• Can I fine-tune models with my own data?

  Yes. You can upload datasets, launch fine-tuning jobs, and deploy the resulting checkpoints to production.

• How do I control costs in production?

  Use quotas, rate limiting, model selection, and prompt optimization, and monitor usage and latency in the dashboard.

• What modalities are supported?

  Together AI supports text chat, image generation and understanding, code completion, and embeddings.

• Is there an enterprise option?

  Yes. Enterprises can access dedicated clusters, private model hosting, and tailored SLAs.