Ivan Burazin(@ivanburazin):We got cited in the official NVIDIA blog alongside @perplexity_ai @ClickHouseDB and @DeepInfra for the performance results with NVIDIA's new Vera CPU. A couple of weeks ago, the @daytonaio team spent 5 days onsite at @nvidia HQ putting the Vera CPU through agentic workloads on Daytona sandboxes. Results: - serious gains for agentic execution - larger memory bandwidth than traditional server CPUs - wide SVE2 vector units with native FP8 that make NumPy-heavy code fly Agentic workloads have a completely different shape from standard inference. A single session can accumulate hundreds of thousands of input tokens as agents reason, call tools, and spawn sub-agents. That's the same workload profile we've been optimizing Daytona sandboxes for: stateful, long-running, and CPU-heavy vs quick ephemeral containers most people are still building on. Vera is built for this. And Daytona is already ARM-capable, with ARM64 sandboxes rolling out globally soon. Read more:

2026.09.16 14:51

We got cited in the official NVIDIA blog alongside @perplexity_ai @ClickHouseDB and @DeepInfra for the performance results with NVIDIA's new Vera CPU. A couple of weeks ago, the @daytonaio team spent 5 days onsite at @nvidia HQ putting the Vera CPU through agentic workloads on Daytona sandboxes. Results: - serious gains for agentic execution - larger memory bandwidth than traditional server CPUs - wide SVE2 vector units with native FP8 that make NumPy-heavy code fly Agentic workloads have a completely different shape from standard inference. A single session can accumulate hundreds of thousands of input tokens as agents reason, call tools, and spawn sub-agents. That's the same workload profile we've been optimizing Daytona sandboxes for: stateful, long-running, and CPU-heavy vs quick ephemeral containers most people are still building on. Vera is built for this. And Daytona is already ARM-capable, with ARM64 sandboxes rolling out globally soon. Read more: