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Together AI

Run, fine-tune, and scale open-source models: start on cheap shared inference and graduate to dedicated GPUs (including on-demand B200s) as traffic grows.

Developer Tools
4.5freemium

The verdict on Together AI: Developers who want to run, fine-tune, or deploy open-source models via API without managing GPU infrastructure Together AI's pitch is full open-model lifecycle through one API: run inference, fine-tune, and scale to production on 200+ models across major open-source families, with dedicated GPU options including on-demand B200s when shared infrastructure isn't enough. Pricing: Pay-as-you-go from $1.04/M tokens / dedicated GPUs from $6.49/hr. Last reviewed: August 2026.

Best For

Developers who want to run, fine-tune, or deploy open-source models via API without managing GPU infrastructure

Standout Feature

A catalog of 200+ open models across major families, all accessible through one OpenAI-compatible interface

TL;DR

Competitive pricing and real production scale, usage costs are worth modeling before committing to heavy workloads.

Alternatives

Overview

Together AI is a cloud platform for running, fine-tuning, and deploying open-source AI models, offering an API-first approach to the full open-weight model lifecycle at competitive pricing compared to closed-model providers. Its inference catalog includes 200+ models across major open families, Llama, Mistral, Qwen, DeepSeek, Stable Diffusion, FLUX, accessible through an OpenAI-compatible API that enables switching to open models without application code changes. Together's fine-tuning service handles supervised fine-tuning, LoRA fine-tuning, and full model fine-tuning on custom datasets, with managed training infrastructure that eliminates the need for GPU cluster management. The fine-tuned model is then deployable through the same inference API for seamless production use.

Together's pricing undercuts OpenAI and Anthropic on comparable capability tiers by 5–10x in many cases, making it cost-effective for high-volume inference that would be prohibitively expensive on closed-model APIs. The Playground provides model comparison and prompt testing across the full catalog. Dedicated endpoints provide reserved capacity for production applications with guaranteed throughput. Together is commonly used by companies that want frontier-quality inference at open-model prices, teams fine-tuning domain-specific models for specialized applications, and developers prototyping with multiple model families before committing to a production architecture.

Our Take

The OpenAI-compatible interface means low switching friction for existing code. Usage costs add up at heavy workloads, so it's worth modeling your token volume before committing to it as a production platform. The right fit is a developer or team who wants the breadth and control of open-source models without building or managing GPU infrastructure themselves.

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Key Features

  • Inference for 200+ open models
  • Fine-tuning and training
  • OpenAI-compatible API
  • Dedicated endpoints
Pros
  • Broad open-model catalog
  • Scales for production
  • Competitive pricing
Cons
  • Usage costs add up
  • Less consumer-facing

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