Together AI

Developer Tools

Together AI

PaidAPI

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The AI Native Cloud: serverless inference across 200+ open models (DeepSeek, Llama, Qwen and more), plus fine-tuning and GPU clusters. Pay per token with 50% off batch inference

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Our Verdict

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The default on-ramp for running open-source models in production

Together AI has quietly become the answer to a very common question: how do we use open-source models without hiring an infrastructure team? The catalog is enormous and refreshingly current — new DeepSeek, Qwen or Llama releases show up within days — the API speaks fluent OpenAI so migration is a one-line change, and the pricing ladder is honest: free models to prototype, cheap serverless tokens to launch, dedicated endpoints when latency matters, and $1.49/hr GPU clusters when you outgrow all of it. The research pedigree behind FlashAttention shows up as real-world speed rather than marketing. The trade-offs are structural, not incidental: there are no proprietary frontier models here, so peak-capability workloads still belong elsewhere, and the per-model pricing spread rewards teams that actually watch their bills. Rivals like Fireworks and Groq win specific races on speed or niche models. But as the single vendor most likely to have the open model you want, at a fair price, behind an API you already know — Together is the safest first pick in the category.

Best for

•Teams moving from closed-model APIs to open models for cost or control
•Developers who want one API covering LLMs, vision and image models
•Startups fine-tuning and serving custom models without owning GPUs

Consider alternatives if

•You need frontier-model capability above all (→ OpenAI / Anthropic / Gemini APIs)
•Your workload is generative media rather than LLMs (→ Fal.ai / Replicate)

Try Together AI

Supported Platforms

Web AppAPI

Available platforms include Web App and API.

Key Features

Serverless inference for 200+ open-source models: Llama, DeepSeek, Qwen, Kimi and more

OpenAI-compatible API — switch providers by changing one base URL

Fine-tuning service with LoRA and full-parameter options

Dedicated endpoints with per-minute GPU billing for steady workloads

GPU clusters (H100/H200/B200) rentable from $1.49/hr for training

Batch inference at 50% discount plus a free tier of models to prototype on

Pricing

free

A free tier of selected models (including Llama-family endpoints) lets you build and test without a credit card; new accounts also get starter credits.

paid

Pay-as-you-go token pricing roughly from $0.03 to $4.50 per million tokens depending on model size; batch inference is 50% off; dedicated endpoints bill GPU time per minute; GPU clusters start at $1.49/hr per GPU with reserved discounts. (Verified against the official pricing page, 2026-07-28.)

Use Cases

Running open-source LLMs in production without managing GPUs

Cutting inference bills by swapping GPT-class calls to open models

Fine-tuning Llama/Qwen-class models on proprietary data

Training runs on rented H100/H200 clusters without long contracts

Pros

One of the broadest open-model catalogs, updated within days of releases

Serious research pedigree (FlashAttention lineage) shows in inference speed

Full ladder from free tier to serverless to dedicated GPUs to clusters

Transparent per-token pricing that routinely undercuts closed-model APIs

Cons

No proprietary frontier models — you trade peak capability for cost and control

Per-model pricing spread means bills need monitoring as you switch models

Dedicated endpoints and clusters push you into infrastructure decisions

Fierce competition (Fireworks, Groq, DeepInfra) keeps feature parity shifting

Latest Update

2026: Together AI keeps racing model releases — DeepSeek, Qwen, Kimi and Llama variants appear on the platform within days — while building out the compute ladder: batch inference at half price, fine-tuning upgrades, and B200/H200 GPU clusters from $1.49/hr alongside its serverless API.