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For agents: Nscale docs for serverless AI inference models (chat, vision, embeddings), a quickstart, and a Workbench for experimenting with and comparing models.
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The beginning of the file, from our validated copy saved 2026-10-27T17:57:56.447Z. Cached copy · Source on nscale.com
# Nscale
- [Overview](https://docs.nscale.com/docs/getting-started/overview.md): Welcome to the Nscale docs. Discover how to get started and unlock the full potential of Nscale.
- [Quickstart](https://docs.nscale.com/docs/getting-started/quickstart.md): Get up and running with Nscale’s serverless inference models in just a few steps. This guide will walk you through signing up, adding credit to your account, and making your first API call to start leveraging the power of our AI models.
- [Quick search](https://docs.nscale.com/docs/getting-started/quick-search.md): Find any resource, page or command in the console from the keyboard. Search by name, ID, IP address, MAC address or hostname, narrow results with filters, and jump straight to what you need.
- [Workbench](https://docs.nscale.com/docs/ai-services/workbench.md): Experiment with models, save and compare presets, and view costs.
- [Serverless models](https://docs.nscale.com/docs/ai-services/models.md): Explore the models currently available for serverless inference, ready to deploy instantly for chat, vision, embeddings and image generation.
- [Chat](https://docs.nscale.com/docs/use-cases/chat.md): This guide will walk you through integrating a chat model into your application using Nscale’s API. With our serverless architecture, you can focus on building your application without worrying about infrastructure management.
- [Image Generation](https://docs.nscale.com/docs/use-cases/image-generation.md): This guide will walk you through integrating image generation models into your application using Nscale's API. With our serverless architecture, you can focus on building your application without worrying about infrastructure management.
- [Deploy a model](https://docs.nscale.com/docs/dedicated-models/deploy-a-model.md): Run a model in your environment and call it with an OpenAI-compatible endpoint.
- [Evaluations (coming soon)](https://docs.nscale.com/docs/ai-services/evaluations.md): Coming soon
- [Environments](https://docs.nscale.com/docs/platform-services/environments.md): Reuse your GPUs across multiple environments, such as dev, staging, and prod, and deploy AI models into each one.
- [Managed Kubernetes](https://docs.nscale.com/docs/platform-services/managed-kubernetes.md): Create and run single-tenant Kubernetes clusters on on-demand or reserved GPU capacity with Nscale Kubernetes Service (NKS).
- [File storage on NKS](https://docs.nscale.com/docs/platform-services/nks-file-storage.md): Give pods on an Nscale Kubernetes Service (NKS) cluster shared, persistent, POSIX filesystem storage with Nscale file storage and PersistentVolumeClaims.
- [Clusters](https://docs.nscale.com/docs/compute/clusters.md): This guide provides step-by-step instructions to help users create, manage, and monitor virtual machines within the Clusters. It covers how to select VM configurations, choose system images, connect to project-level networks, and perform lifecycle actions. The guide is designed to suppor
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