Deploy DeepSeek V4-Flash on Alibaba Cloud PAI-EAS

Learn how to deploy DeepSeek V4-Flash on Alibaba Cloud PAI-EAS. Get to know the four different approaches — Token API, PTU, Model Unit (MU), and Bare Metal GPU. We compare pricing models, walk through a real PAI-EAS deployment from scratch, and run head-to-head benchmarks to show you the best performance per dollar. Whether you're building an AI-powered SaaS product, running an inference pipeline, or evaluating cloud GPU options, this video gives you the real numbers to make the right decision. Resources mentioned in this video: Model Studio Console: https://int.alibabacloud.com/m/1000413252/ PAI-EAS Documentation: https://int.alibabacloud.com/m/1000413260/ PAI-EAS Model Gallery: https://int.alibabacloud.com/m/1000413276/ Model Studio Token Plan Overview: https://int.alibabacloud.com/m/1000413268/ DeepSeek V4 Technical Report (PDF): https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro/blob/main/DeepSeek_V4.pdf Model Studio DeepSeek API Reference: https://int.alibabacloud.com/m/1000413284/ Article: https://int.alibabacloud.com/m/1000413474/ Like & Subscribe for more AI content! 0:00 - Introduction 0:55 - Pricing Models Compared: Token API, PTU, Model Unit & GPU 5:00 - What Is DeepSeek V4-Flash? 7:28 - Using Model Studio with Token-Based API 8:10 - Overview of PAI-EAS (Elastic Algorithm Service) 9:13 - Preparing Cloud Resources for Deployment 14:25 - Step-by-Step: Deploying DeepSeek V4-Flash on PAI-EAS 20:25 - Retrieving Your API Key & Endpoint 24:10 - Running the Performance Benchmark 26:35 - Interpreting Benchmark Results #AI #DeepSeek #PAI #ModelStudio #Tutorial #LLMs #Token #GPUInference