NVIDIA Dynamo 1.0 can 7x your inference performance. Your OS determines whether you get there.

On March 16, NVIDIA announced Dynamo 1.0. This production-grade, open-source platform functions as the operating system for AI factories, orchestrating GPU and memory resources across clusters to handle inference workloads at scale.

On identical Blackwell GPU hardware, Dynamo 1.0 delivers up to 7x higher inference throughput, which is a significant performance gain over previous iterations. During GTC 2026, NVIDIA demonstrated it live, and inference providers running the same infrastructure saw token generation speeds jump from 700 to nearly 5,000 per second (after NVIDIA updated their software stack).

Same hardware. Seven times the output. That’s the headline, but here’s what the headline leaves out: Dynamo 1.0 is a software optimization layer; it disaggregates the inference pipeline, intelligently routes requests, manages KV cache across the cluster, and moves data between GPUs efficiently. Dynamo 1.0 is sophisticated, well-engineered, and genuinely capable of the performance gains NVIDIA demonstrated. It is also entirely dependent on the foundation underneath it.

For Dynamo to deliver its full performance advantage, the OS layer it runs on must meet a specific set of conditions: the CUDA stack must be validated and current, the DOCA-OFED networking stack must be clean and compatible, and the kernel must be stable and free of the conflicts that accumulate when drivers are installed and updated manually over time. If any of those conditions are not met, Dynamo's optimization layer works against headwinds that the hardware never created.

An OS assembled from unvalidated packages, patched manually, and maintained reactively is not a neutral base for Dynamo, and quickly becomes a performance ceiling.

This is exactly the problem RLC Pro AI was built to eliminate.

RLC Pro AI ships with the NVIDIA CUDA Toolkit and DOCA-OFED stack pre-validated, tested together as a cohesive system, and ready to run. With RLC Pro AI, there is no manual driver installation, no version compatibility questions, and the kernel and networking stacks are selected and validated in combination, which means Dynamo 1.0 inherits a clean foundation rather than spending its optimization budget working around infrastructure debt.

The organizations that will realize the full 7x improvement Dynamo delivers are the ones running it on infrastructure that was built for it. The organizations running Dynamo on top of a distribution that was not designed for production AI inference will see minimal improvement, but not nearly what’s possible with RLC Pro AI.

The gap between those two outcomes lives at the OS layer.

Everyone running inference at scale is hardware-constrained, and GPU availability does not keep pace with demand. The 7x Dynamo performance gain on existing hardware is not a minor optimization. At scale, this performance gain is the difference between buying more GPUs and getting more out of the ones you have. Spend more money or use your current hardware more wisely: the choice is obvious.

RLC Pro AI is the Enterprise Linux built to make sure that gain is not left on the table.

Learn more about RLC Pro AI and Dynamo compatibility at ciq.com/products/rocky-linux/pro/ai/