Run any ML workload (PyTorch, Ray, Spark, and more) with 100x faster iteration loops and without thinking about infrastructure. Cost-optimization, fault-tolerance, and push-button scaling are built in.

Pythonic and YAML-free

Kubernetes Native

Magical Instant Iteration

Robust Production Toolchain

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Powerful compute at your fingertips

Iterate and debug natively

Distributed ML without the lift

Research-to-production, instantly

Durable execution in production

Docs

Github

Skip the lift

"Faster, please"

50% off your compute bill

LoRA Fine-Tune Llama 3

Training

Multi-GPU DeepSeek-R1 with vLLM

Batch Inference

Continual Recommender (DLRM) Training with Ray

Composite Systems

Parallel GPU Batch Embeddings

Data Processing

Search & Sharing

Observability

Auth & Access Control

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Finally, powerful AI training that's rapid enough for development and robust enough for production.

Kubetorch: Pythonic AI/ML development at scale