What is Together AI?

Together AI is a cloud platform for running, fine-tuning and deploying open-weight AI models rather than a single closed model behind an API. It hosts models like Llama, DeepSeek, Qwen, GLM and Gemma variants for inference, offers fine-tuning services, and rents GPU capacity — from serverless pay-per-use inference up to dedicated H100, H200 and B200 clusters — for teams that want more control over cost and model choice than a single-vendor API provides.

Who it is for

Together AI is built for developers and ML teams who want to use open models instead of, or alongside, closed models like GPT or Claude — often to cut inference costs, fine-tune on proprietary data, or avoid dependency on a single model vendor. It also serves teams that need raw GPU compute for training or high-volume inference and don't want to manage their own hardware. It's less relevant for teams that only need occasional API calls and are happy paying a closed-model provider's premium for convenience.

Key features

Serverless inference — pay-per-use access to chat, vision, embeddings, image, video and audio models with no infrastructure to manage
Wide open-model catalog — hosts current-generation open models including Llama, DeepSeek, Qwen, GLM and Gemma variants, updated as new releases ship
Fine-tuning — customize open models on your own data rather than relying only on prompting
Provisioned throughput — reserve dedicated capacity at a fixed monthly cost for predictable high-volume workloads, sized by a pricing tool based on traffic patterns
Dedicated GPU instances — single-tenant H100 and B200 hardware with guaranteed performance for latency-sensitive or compliance-driven use cases
On-demand and reserved GPU clusters — H100, H200 and B200 clusters billed hourly, with reserved discounts for longer commitments
OpenAI-compatible API — lets teams swap in Together AI with minimal code changes if they're already built against an OpenAI-style client
Sandbox and code interpreter — usage-billed compute environments for running generated code safely

Pricing

Together AI is usage-based across every layer of the platform. Serverless inference for chat, vision and embeddings models is priced per million tokens and varies by model (roughly $0.0015 to $4.50 per million input tokens depending on model size and capability), with image generation billed per image and video and audio priced separately. Fine-tuning is billed per token processed, varying by model and method. GPU rental ranges from around $1.99/hour for preemptible H100 capacity up to $8.99/hour for on-demand B200 instances, with reserved pricing dropping further for longer commitments. Because pricing spans so many models and hardware types, exact current rates should be checked on Together's pricing page for the specific model or GPU you plan to use.

Strengths

The breadth of open models available in one place is a real advantage — teams can compare Llama, DeepSeek, Qwen and other options without integrating multiple separate providers, and switching models often requires only a config change thanks to the OpenAI-compatible API. Pricing is genuinely competitive against closed-model APIs for comparable quality on many tasks, and the option to move from serverless inference to dedicated GPUs as usage grows means teams don't have to re-platform as they scale. Fine-tuning support on open models also gives teams a path to real customization that closed-model APIs don't always allow.

Weaknesses

Together AI only hosts open-weight models, so teams that specifically need GPT-4-class or Claude-class closed models will still need a separate provider alongside it. Popular models can occasionally hit capacity limits during high demand, which matters for latency-sensitive production workloads. The pricing structure, while competitive, is also complex — with separate rates for serverless tokens, provisioned throughput, dedicated instances and GPU clusters — so estimating true monthly cost for a given workload takes more effort than a single flat-rate API price.

Getting started

Create an account at together.ai, generate an API key, and call any hosted model through the OpenAI-compatible endpoint or Together's own SDK. Fine-tuning jobs and dedicated GPU or cluster reservations are configured through the dashboard, where a pricing tool helps estimate provisioned throughput needs based on expected traffic.

Verdict

Together AI is a strong pick in LLM APIs & Developer Platforms for teams committed to open models who want competitive pricing and a path from serverless inference to dedicated infrastructure. Teams that need closed frontier models alongside open ones should also compare it with OpenRouter or a direct provider like OpenAI API to cover both bases.