Dedicated Model Inference
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.
Build with leading models
Explore top-performing models across text, image, video, code, and voice.
Have your own model?
Deploy custom containers on Together’s managed GPU infrastructure with automatic scaling, job queues, and built-in observability.
Key capabilities, purpose built for AI natives
Scale from self-serve instant clusters to thousands of GPUs, all optimized for better performance with Together Kernel Collection.
Cut latency on dedicated infrastructure with ATLAS — Together's AdapTive-LeArning Speculative System. Predict and validate multiple tokens per step to accelerate workloads continuously. No decoding bottlenecks.
Launch dedicated endpoints in minutes by selecting a target model and hardware configuration. Establish production-ready inference environments without requiring deep infrastructure expertise.
Deploy custom models directly from Hugging Face or S3 onto dedicated endpoints via the UI or CLI. Maintain complete ownership while offloading infrastructure management.
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
- Static Speculator
- No Speculator
ATLAS performance
3.18x faster
ATLAS, our AdapTive-LeArning Speculator System, continuously learns from live traffic — outperforming static speculators and specialized hardware.
learn moreCPD improves sustainable QPS by 35-40%
- CPD
- Baseline
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%.
learn moreOutput speed
- Megakernel (H100)
- Baseline (B200)
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.
learn moreBF16 all-reduce sum performance (on 8x NVIDIA B200s)
- PK
- NCCL
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.
learn more
Deployment options
Run models using different deployment options depending on latency needs, traffic patterns, and infrastructure control.
Real-time
A fully managed inference API that automatically scales with request volume.
Best for
Batch
Process massive workloads of up to 30 billion tokens asynchronously, at up to 50% less cost.
Best for
Dedicated Model Inference
An inference endpoint backed by reserved, isolated compute resources and the Together AI inference engine.
Best for
Dedicated Container Inference
Run inference with your own engine and model on fully-managed, scalable infrastructure.
Best for
Production-grade
security and data privacy
We take security and compliance seriously, with strict data privacy controls to keep your information protected. Your data and models remain fully under your ownership, safeguarded by robust security measures.
NVIDIA preferred partner
AICPA SOC 2 Type II
Customers running inference in production
6×
cost reduction
<400ms
p95 model latency
Weekly
model deployments
"Low latency is especially important for voice because there’s a much higher UX bar. Together helped us push latency down by optimizing our models with techniques like speculative decoding, and they’ve been a reliable production partner — proactive about risks and fast when issues come up."
~30%
Cost savings
"Together has helped us deploy VyUI, our state-of-the-art computer AI model. We had multiple in-depth meetings where we brainstormed how we could satisfy our model's custom technical requirements while still leveraging Together's infrastructure for efficient, load-balanced inference."
"Together AI offers optimized performance at scale, and at a lower cost than closed-source providers – all while maintaining strict privacy standards."