Breaking

NVIDIA Dynamo 1.0 Enters Production as Distributed Inference Framework for AI Factories

October 18, 2026 at 13:06 EDT

Foundation Models
Infra & Chips
Open Source

NVIDIA has released Dynamo 1.0, an open-source distributed inference platform designed to scale large language model endpoints across Kubernetes clusters using disaggregated compute workers and OpenAI-compatible APIs. The framework addresses a critical operational gap: how to efficiently run reasoning models at datacenter scale without massive infrastructure complexity.

NVIDIA Dynamo 1.0 Released

Disaggregated Inference Scales LLM Serving 7× on Blackwell

Open-source framework separates prefill and decode workers for independent scaling, achieving 3,200 tokens per second throughput and 85ms time-to-first-token in production.

7×

Requests Served on Blackwell

3,200

Tokens/Second Throughput

85ms

Time to First Token

4×

Faster Interactivity (gpt-oss-120b)

Throughput Comparison: Disaggregated vs Monolithic

820

Monolithic

3,200

Disaggregated

2 prefill + 2 decode workers (vLLM baseline)

Key Features

Kubernetes-native DGDR custom resource with hierarchical architecture
OpenAI-compatible API + Anthropic Messages API support
SLO-based autoscaling via time-series forecasting
Multi-backend support: vLLM, TensorRT-LLM, SGLang
Agentic workload optimization: 4× lower TTFT, 1.5× higher throughput
12+ confirmed production deployments (ByteDance, DigitalOcean, CoreWeave, etc.)

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