# inference

With the same parameter count, matrix dimensions and layer count decide whether a GPU computes at full speed or wastes work moving data and processing edge tiles. Near-square dimensions aligned to 128, 256, or 512—and often wider, shallower models—fit hardware better without sacrificing accuracy.

SemiAnalysis benchmarked ~1,000 GPUs across NVIDIA and AMD lineups. GB300 NVL72 hits 100x over H100 — Jensen's 30x was an underestimate. AMD FP8 competes, but FP4+disagg+wideEP combo falls apart in software.

Artificial Analysis launches AA-AgentPerf, a hardware benchmark that uses real coding agent trajectories instead of synthetic queries. It allows production optimizations, measures per-accelerator/per-kW/per-dollar efficiency, and scales from single cards to full racks.

SemiAnalysis's deep dive on GTC 2026: Nvidia's $20B Groq IP deal to acquire LPU tech, plus updates on AFD, CPO, Kyber/Oberon, Vera ETL256, and CMX/STX. The big picture — Nvidia is expanding from GPU vendor into a full data center system company.

NVIDIA released Nemotron 3 Super, a 120B parameter open-source reasoning model with only 12B active parameters. It combines Mamba and Transformer in a hybrid MoE architecture, scores 36 on the Intelligence Index, and runs at a blistering 484 tok/s.

OpenAI released GPT-5.3-Codex-Spark, its first model on Cerebras chips. It's incredibly fast (>1000 tokens/sec, 80% lower latency), but smaller, no auto-tests, Pro-only. This marks OpenAI's first production deployment on non-Nvidia hardware, redrawing the AI compute landscape.