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Together AI

by Together AI · Platform · also known as Together, Together Cloud, together.ai

Cloud platform for open-source models: serverless and dedicated inference, fine-tuning, GPU clusters, batch jobs and code sandboxes behind an OpenAI-compatible API

ProprietaryUsage-basedEnterpriseCloud
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Link verified Nov 2, 2026

Overview

Together AI is a cloud platform for running, training and serving open-weight models. Serverless inference exposes a large catalog of language, reasoning, speech, image and video models through an OpenAI-compatible API, billed per token or per media unit; dedicated endpoints give single-tenant GPU instances billed per GPU-hour; and fine-tuning jobs (supervised and preference-based) train on your data before deployment. Further services include provisioned throughput, batch inference, evaluations, code sandboxes and a code interpreter, and reserved or on-demand GPU clusters with attached storage for training at scale. Official Python and TypeScript SDKs mirror the API.

The catalog spans families such as Llama, Qwen, DeepSeek, Kimi, GLM, Mixtral, gpt-oss and Gemma for text, Whisper for speech and FLUX among image models, which makes Together a common choice for teams who want open models without operating vLLM themselves or who need burst GPU capacity. Pricing is usage-based throughout, with enterprise terms for reserved capacity. Limits are those of a hosted provider: data is processed off-premises, the catalog changes as models are added or retired, and heavy sustained use may be cheaper on owned hardware.

Capabilities

  • Serverless inference on open-weight text, speech, image and video models
  • Dedicated single-tenant endpoints billed per GPU-hour
  • Supervised and preference fine-tuning with deployment
  • Batch inference, provisioned throughput and evaluations
  • Code sandboxes and code interpreter
  • On-demand and reserved GPU clusters
  • OpenAI-compatible API with Python and TypeScript SDKs

Typical workflows

  1. Serve a Qwen or Llama model to an application without managing GPUs
  2. Fine-tune an open model on domain data and deploy it to an endpoint
  3. Rent a GPU cluster for a short training run

Strengths

  • Wide open-model catalog under one API
  • Path from serverless to dedicated to clusters
  • OpenAI compatibility eases migration

Limitations

  • Hosted only
  • Catalog and prices change frequently
  • Sustained high volume may favor self-hosting

Prerequisites

  • Together AI account and API key

Who it is for

  • Developers using open models without infrastructure
  • Teams fine-tuning open models
  • Researchers needing short-term GPU capacity

Alternatives & comparison

  • Axolotl

    YAML-configured open-source framework for fine-tuning and post-training LLMs: full, LoRA and QLoRA training, preference and RL methods, multimodal models and multi-GPU or multi-node runs

    Open sourceOpen source
  • GroqCloud

    Low-latency hosted inference API for open-weight models on Groq's LPU hardware, OpenAI-compatible, with speech-to-text, text-to-speech, tool use and batch tiers

    ProprietaryUsage-based
  • Hugging Face Hub

    Hosting platform for open models, datasets and Spaces demo apps built on git repositories and Xet storage, with Inference Providers, Endpoints, Jobs and an open-source Python client and CLI

    MixedFreemium
  • Mistral AI

    French model provider offering open-weight and proprietary models through the Studio API, OCR and speech models, the Vibe agent for productivity and coding, and self-deployment options

    MixedFreemium
  • OpenAI API

    OpenAI's hosted developer platform: Responses and Chat Completions APIs, Realtime voice, embeddings, images, audio, fine-tuning, evals and managed agents

    ProprietaryUsage-based
  • OpenRouter

    Unified API gateway to hundreds of models from many providers with automatic fallbacks, credit-based pass-through billing, BYOK, free models and data-policy routing

    ProprietaryFreemium
  • vLLM

    High-throughput LLM inference and serving engine with PagedAttention, continuous batching, quantization and an OpenAI-compatible server for GPU and accelerator clusters

    Open sourceOpen source
Compare Together AI with its alternatives →

Sources & verification

Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.

Confidence
High
Reviewed
Nov 1, 2026
Links
Verified · Nov 2, 2026

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