MLPerf Inference v6.1 is out, and we have two firsts: the first agentic inference workload on datacenter hardware, and the first MLPerf deployment of a model over a trillion parameters. On 4x NVIDIA Blackwell Ultra GPUs, we posted the leading Offline throughput on GPT-OSS 120B among all Blackwell Ultra GPU submissions, plus an 8.85% throughput gain over v6.0 on identical hardware. That's six months of pure software optimization. On NVIDIA HGX B200, we swapped in Kimi K2.6 for the open-division agentic benchmark, running a 1T+ parameter model where the reference workload expects 27B. Same harness, no memory ceiling. Full results and methodology in the blog. Link below. 📷 ↧
published
MLPerf Inference v6.1 is out, and we have two firsts: the first agentic inference workload on datacenter hardware, and the first MLPerf deployment of a model over a trillion parameters. On 4x NVIDIA Blackwell Ultra GPUs, we posted the leading Offline throughpu
$LINK
Open the original public source →
Latest documented BWB result
See Billy's timestamped results and follow-through.
Review the latest gains posts, original timestamps, and proof images published by Banking With Billy.
Historical results are not a promise of future performance. Trading involves substantial risk.This public post is a timestamped information archive, not personalized financial advice. Alerts can change as markets move. Join Billy's private group for the complete daily stream and follow-through.