💡 NVIDIA Vera is the CPU for agents and benchmark results from DeepInfra show that it's more than 2x as fast compared with other CPUs. Read the results ⤵️
🚀 We run AI agents in production so when NVIDIA built Vera CPU specifically for agents, we measured it ourselves rather than relying on the spec sheet. NVIDIA Vera CPU(88 Olympus cores, the CPU side of the upcoming Vera Rubin platform) is designed around a real shift: agentic AI turns inference into a loop, and the CPU executes all the work around each model call orchestration, parsing, sandboxed code execution, data movement. When the CPU is slow, the agent waits. We got early access to Vera and tested it with our own harness: a real agentic workload from our production environment, real traffic replayed at fixed pacing (zero live tokens, so every difference is the CPU), and an identical fair configuration across four architectures NVIDIA Vera, AMD Zen5, Intel Granite Rapids, Intel Sapphire Rapids. What we found: → NVIDIA's public claim is “80% faster agentic CPU performance” (a 1.8× bar). We locked our comparison basis before measuring Vera. Measured result: 1.8x on orchestration over best x86 CPU and the fastest of all four architectures tested. → Vera swept every workload category, orchestration, code-execution spawn, memory bandwidth, and base throughput where no single incumbent had dominated. → At a strict QoS bar, Vera sustained 256 concurrent agents per partition vs 160 for incumbents: 1.33–1.6× more agents per core. → With the agent fleet at full load, we served a real LLM on the 56 leftover cores at 118.5 tok/s, more than a full 72-core Grace socket doing nothing else. The mechanism is real per-core execution: 3.62 IPC on branch-heavy work versus 2.44 for the best measured x86 (Intel; AMD Zen5 had no IPC capture) Full technical write-up, including methodology: → https://lnkd.in/g9ryzh_8
