Qwen 3.5 AI Agents on GPU and CUDA: The Engineer's Guide to Mastering Hardware Sizing, Local LLM Inference, Optimize VRAM, Building and Scaling Native Multimodal AI in Production

Deploy trillion-scale intelligence on real GPUs, not theory, not hype, but production-grade AI systems engineered for performance.If you want to run Qwen 3.5 models on GPU infrastructure, optimize CUDA kernels, manage VRAM like a systems engineer, and deploy scalable AI agents in production, this book gives you the blueprint.This guide teaches you how to:Deploy Qwen 3.5 models (35B-A3B, 122B-A10B, 397B-A17B) on real GPU hardwareOptimize inference using CUDA, Triton kernels, and memory tuningCalculate VRAM requirements and KV cache budgets accuratelyRun high-performance inference with vLLM and SGLangContainerize and scale using Docker and KubernetesBuild multimodal AI pipelines (text + vision)Design and orchestrate multi-agent systemsMonitor GPU telemetry and production workloadsAbout the TechnologyQwen 3.5 introduces advanced Mixture-of-Experts (MoE) architecture that activates only a subset of model parameters per token, enabling massive scale without linear compute costs.Inside this book, you’ll understand:Sparse expert routingCUDA acceleration strategiesGPU parallelism and tensor optimizationVRAM allocation modelingProduction inference pipelinesInfrastructure scaling for enterprise AIBook SummaryQwen 3.5 AI Agents on GPU & CUDA is a hands-on engineering guide for deploying large-scale AI systems with production-grade performance. It bridges the gap between theoretical model architecture and real-world GPU execution, showing you exactly how sparse MoE models run efficiently on modern hardware.From VRAM math and KV cache planning to containerized inference stacks using vLLM, SGLang, Docker, and Kubernetes, this book provides a structured path to building scalable, multimodal, high-performance AI agents. Whether you're optimizing CUDA memory transfers or orchestrating distributed inference across GPUs, you’ll gain the clarity and confidence to deploy advanced models in enterprise environments.What’s Inside This Book?Deep dive into Qwen 3.5 MoE architectureStep-by-step GPU deployment workflowsCUDA optimization and performance tuningVRAM and KV cache calculation strategiesMultimodal vision tokenization integrationMulti-agent orchestration frameworksProduction monitoring and GPU telemetryThis book is designed for:AI engineersMachine learning practitionersSystems architectsInfrastructure engineersGPU performance optimizersAdvanced developers scaling LLM If you're ready to deploy Qwen 3.5 models with precision, optimize GPU performance, and build scalable AI agents that operate in real-world production environments, this book will give you the competitive edge.Build smarter. Deploy faster. Engineer AI the right way.Get your copy today and start running large-scale AI on GPU infrastructure with confidence Read more