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NVIDIA Dynamo 1.0 Reaches Production, Delivers 7x Throughput Boost for Multi-Node Inference
· releasefeatureplatformperformanceapi · developer.nvidia.com ↗

Production-Grade Distributed Inference at Scale

NVIDIA Dynamo 1.0 is now available as a mature, production-grade distributed inference framework designed for deploying large-scale, multi-node AI models. The platform addresses the critical challenge of orchestrating reasoning models and agentic AI workflows across multiple GPU nodes, delivering low-latency, high-throughput inference for real-world production environments.

Proven Performance and Adoption

Dynamo demonstrates significant performance gains: it boosts inference throughput by up to 7x on NVIDIA Blackwell hardware, as validated by recent SemiAnalysis InferenceX benchmarks (DeepSeek R1-0528, FP4). The framework has already been deployed in production by a diverse set of organizations including AstraZeneca, ByteDance, CoreWeave, DigitalOcean, Gcore, Meituan, Pinterest, SoftBank Corp., Tencent Cloud, and Together AI. It has also been integrated into managed Kubernetes environments by Alibaba Cloud, AWS, Google Cloud, Microsoft Azure, and Oracle Cloud Infrastructure.

Key Capabilities and Features

Core Capabilities:

  • Supports leading open-source inference engines: SGLang, NVIDIA TensorRT LLM, and vLLM
  • Validates production readiness through independent benchmarks (MLPerf, SemiAnalysis InferenceX)
  • Seamless integration with major cloud platforms and Kubernetes environments

Recent Enhancements:

  • Agentic Inference Optimizations: Priority-based routing and cache pinning for improved multi-request handling
  • Multimodal Acceleration: Disaggregated encode/prefill/decode pipelines, embedding caching, and multimodal key-value routing
  • Video Generation Support: Native integration with video-generation models
  • ModelExpress: Accelerates model startup 7x faster through checkpoint restore and weight streaming via NVIDIA NVLink
  • Advanced Orchestration: Grove API for topology-aware GPU scheduling on NVIDIA GB300 NVL72
  • Zero-Config Deployment: DGDR support for simplified cluster setup
  • Resilient Inference: Layered fault detection, request cancellation, and request migration capabilities
  • KV Block Manager: Pip-installable module with object storage integration for flexible deployment

Getting Started

Developers can deploy Dynamo across multiple nodes to serve reasoning models, multimodal inference, and agentic AI workflows at scale. The framework's flexible architecture accommodates various inference engines and deployment patterns, making it suitable for both cloud and on-premises environments.