Anyscale
About Anyscale
Anyscale provides a platform for scaling distributed training, multimodal data curation, embedding generation, and post-training workloads. The platform is powered by Ray, described as an AI compute engine. Anyscale was built as production-ready Ray. The company helps AI teams build foundation models and run data and serving workloads around them. Users can scale existing AI libraries such as PyTorch, vLLM, SGLang, and XGBoost across many nodes using Python APIs.
Products
- Multimodal data curation: Provides large-scale pipelines for curating and preparing multimodal data across videos, images, text, and audio.
- Distributed model training: Orchestrates model training across GPU clusters with elastic scaling, preprocessing, and GPU observability.
- Batch embedding generation: Processes and generates embeddings at scale for search, retrieval, or training use cases.
- Post-training: Runs LLM inference and training on post-training frameworks like SkyRL and veRL, built on Ray.
- Anyscale Runtime: A managed, Ray-compatible runtime supported by Ray experts for building and running workloads in production.
Used for
- Curating and preparing multimodal data across videos, images, text, and audio
- Orchestrating distributed model training across GPU clusters
- Generating embeddings for search, retrieval, or training
- Running LLM inference and training on post-training frameworks
- Fine-tuning a visual language model on a multi-GPU cluster
Who it is for
- Foundation model builders
From Anyscale's own website, read 2026-10-23. How we build listings.
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