Applied Compute Training
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Introduction
AI Supercloud for training, serving, and improving open models with dedicated infrastructure.
Listed on
August 30, 2026
What is Applied Compute Training?
Applied Compute Agent Cloud (AC2) is a training and inference cloud platform for open-weight models. It enables companies to build custom models using their own data, deploy them at scale, and continuously improve them. The platform is used by enterprises like Microsoft, NVIDIA, and DoorDash.
How to use Applied Compute Training?
- Start training with a few dozen lines of code using your own harness. Use the AC2 console to monitor rollouts, compare runs, and iterate on graders. Deploy models to dedicated inference capacity with autoscaling, and promote checkpoints to production instantly. Leverage Ari, the applied research agent, to analyze results and improve data for the next experiment.
Core features of Applied Compute Training
- Post-train tool-using, long-horizon agents
- Train across text, images, code, and structured data
- Optimize models towards your evals and product KPIs
- Rollout-level observability for debugging
- Model-flexible: upgrade base models without rebuilding stack
- Dedicated inference with zero train-to-deployment mismatch
- Autoscaling replicas and configurable latency/throughput
- Continuous improvement from production traces
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