Introducing Polymorphic Inference, starting with Together Compiler →

Introducing Together Post-Training: Better models, faster runs, lower costs →

Introducing Together Link: Run open models inside the harness you already use →

The Open Source AI Stack: models, inference, routers, harnesses & tools →

GLM-5.3 vs. GLM 5.3 Flash on DeepSWE →

⚡ On-demand B200s now available on Together GPU Clusters →

Explore Research

Research blog

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Together Compiler: Continual Compilation for AI inference

Reyna Abhyankar, Dylan Lim, and Simran Arora

Kernels
To Infinity and Beyond: ThunderKittens Now on NVIDIA Vera Rubin NVL72!

Dylan Lim, Xinyi Li, Sonny Li, Peter Wu, Dan Fu, Simran Arora

Agents
ThunderAgent: 2x Faster Agentic Inference for Synthetic Data Generation at Scale

A program-level scheduler that eliminates KV cache thrashing, delivering more than 2x single-node throughput and near-linear multi-node scaling for large-scale agentic inference.

Hao Kang, Ziyang Li, Weili Xu, Xinyu Yang, Yinfang Chen, Junxiong Wang, Beidi Chen, Tushar Krishna, Chenfeng Xu, Simran Arora.

Kernels
Together AI at ICML 2026: frontier research across the full stack

Nine papers from Together AI and our peers were accepted to ICML 2026 in Seoul. If you are attending come by booth B714. We’d love to connect.

Together Research

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