Hosted inference and GPU clusters for open-source models
Together AI runs open-weight models on its own GPU fleet and sells access through an OpenAI-compatible API. Beyond serverless inference it offers dedicated endpoints, fine-tuning, and rented GPU clusters for teams that want reserved capacity. The catalogue leans toward open models - Llama, Qwen, DeepSeek, Mistral - including large parameter counts that are impractical to self-host. The differentiator is the combination: you can prototype on serverless endpoints, fine-tune a variant, then move the same workload onto dedicated hardware without changing providers.
Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.
open-model serving, fine-tuning, high-volume inference, embeddings at scale
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Mostly open-weight models such as Llama, Qwen, Mistral and DeepSeek, including large parameter counts, plus image and embedding models. The mix changes as new open releases appear.
Yes. You can prototype on serverless endpoints, then reserve dedicated GPUs for the same model when traffic justifies it, without changing providers or rewriting your integration.
For comparable quality it is often cheaper per token, particularly on larger open models. Heavy sustained usage can be cheaper still on reserved capacity, but idle reservations still bill.
Developer console and API keys for the Claude model family
Node-based local interface for running image and video diffusion models
Browser playground for prompting and prototyping with Gemini models
Hosted Jupyter notebooks with optional free GPU and TPU runtimes