Reports
AI-generated structured vendor updates
AMD Unveils Zen 6/7 CPU and MI400/500 GPU Roadmap, Targets NVIDIA Rubin with HBM4 and 2nm
AMD unveiled its Zen 6/7 CPU and MI400/500 GPU roadmap at its 2026 Financial Analyst Day, featuring TSMC 2nm process and HBM4 memory. The MI400 series boasts 432GB memory, 19.6TB/s bandwidth, and 40 PFLOPs FP4 performance, directly targeting NVIDIA's Vera Rubin architecture with an annual cadence to disrupt the AI hardware monopoly.
OpenAI Ends Azure Exclusivity: Model Delivery Control Shifts from Microsoft to Multi-Cloud
OpenAI and Microsoft restructured their partnership in April 2026, ending exclusive Azure licensing and capacity commitments. OpenAI can now serve customers on any cloud; Microsoft retains right of first refusal and revenue share only on its platform. Driven by GPT-5.1's ~3 exaflops inference demand and FTC antitrust scrutiny.
AMD MLPerf 6.0: MI350 GPUs Achieve 3.5x Leap with MXFP4, Debut Multi-Node Training
AMD submitted its most comprehensive MLPerf Training 6.0 results, including first multi-node training (FLUX.1 on 512 GPUs) and MXFP4 training recipe. MI355X delivers 3.5x generational leap over MI300X on Llama 2-70B, within 5% of NVIDIA B200. 10 ecosystem partners validated reproducibility.
AMD and OpenAI Introduce MRC, a Next-Gen Transport Protocol for AI Training
AMD, in collaboration with OpenAI, Microsoft, and other industry leaders, has released the specification for the Multipath Reliable Connection (MRC) protocol. MRC addresses performance bottlenecks of RoCEv2 in hyperscale AI training clusters through intelligent packet spraying, selective retransmission, and network-signaled congestion control, aiming to improve bandwidth utilization and job resilience.
AMD Announces Breakthrough MLPerf Inference 6.0 Results, Showcasing Multinode Scaling and Multimodal Capabilities
AMD's MLPerf Inference 6.0 submission, powered by Instinct MI355X GPUs, surpassed 1 million tokens per second for the first time on models like Llama 2 70B and GPT-OSS-120B. The results highlight efficient multinode scaling, rapid enablement of new workloads (e.g., text-to-video model Wan-2.2-t2v), and reproducible performance across a broad partner ecosystem.