Blog

Announcing our $800M Series C to accelerate the shift to open-source AI
We raised $800M to accelerate the shift to open-source AI. Here's why the economics of closed models don't scale, and what we're building next.

Together AI and Y Combinator partner to launch the first dedicated GPU cluster for the YC community
No more two-year compute contracts. Together AI and YC just gave YC startups a faster way to get GPUs.

DeepSeek-V4 Flash 0731 vs GPT-5.6 Luna on DeepSWE: Cost and Coding
We ran 900 DeepSWE rollouts on DeepSeek-V4 Flash and GPT-5.6 Luna. Luna leads pass@1 by 14 points; DeepSeek delivers 4.8x the solves per dollar.

Together AI at ICML 2026: frontier research across the full stack
Nine papers at ICML 2026 across the full stack. The research that becomes the Together platform. Find us at booth B714 in Seoul.

Kimi K3: The Complete Developer Guide
Kimi K3 is the first open 3T-class model. See how it benchmarks, what it costs, and how to call it on the Together AI API, with copy-paste code examples.

ThunderAgent: 2x Faster Agentic Inference for Synthetic Data Generation at Scale
ThunderAgent is a program-aware scheduler for agentic inference. By treating each agent workflow as a schedulable program, it eliminates KV cache thrashing to deliver more than 2x single-node throughput and near-linear multi-node scaling.

Autoscaling endpoints for LLM inference
GPU utilization can read healthy while your queue backs up, and a new replica takes minutes to warm. Here's how to pick autoscaling metrics, tune scale-up/down windows, and budget for cold starts on dedicated inference.