Dedicated Model Inference | Together AI

Deploy models on dedicated infrastructure, engineered for speed

Purpose-built for teams who need control and the best economics in the market.

## Why Dedicated Inference
with Together AI?

Designed for production workloads that need 
consistent performance and operational control.

Built for production inference

Scale to thousands of GPUs for always-on, production inference deployments.

Industry-leading unit economics

We provide the fastest deployments, enabling best price-performance on top GPUs.

Powered by frontier AI systems research

We continuously roll out the latest innovations to keep your deployments running fast.

Research that ships

Our research team doesn't just publish. They build the optimizations that power every inference request.

ATLAS

CPD

Megakernel

ThunderKittens

Performance on DeepSeek V3.1 (Arena Hard)

ATLAS performance

3.18x faster

ATLAS, our AdapTive-LeArning Speculator System, continuously learns from live traffic — outperforming static speculators and specialized hardware.

Together AI CPD vs 2P1D

+40% throughput

Long-context inference without the latency penalty. CPD (cache-aware prefill-decode disaggregation) separates warm and cold requests, cutting time-to-first-token and boosting throughput by up to 40%.

Megakernel vs baseline

Up to 3.6x faster

Megakernel fuses an entire model's forward pass into a single GPU kernel. Made using the ThunderKittens framework, Megakernel eliminates the idle gaps between operations that rob GPUs of their full potential.

ParallelKittens vs NCCL

Up to 1.79x faster

ParallelKittens—an extension to ThunderKittens for multi-GPU workloads developed in collaboration with Stanford's Hazy Lab—cuts the synchronization overhead that large multi-GPU models pay on every single forward pass.

Build with leading models

Explore top-performing models across text, image, video, code, and voice.

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