AMD's Instinct MI455X, announced at Advancing AI 2026, ships 432GB of HBM4 and 23.3TB/s memory bandwidth on a single card, 2.25x the capacity of the previous-generation MI300 (192GB). When Hugging Face got an early sample, it ran it through 24 core architectures in the Transformers library (covering encoder, decoder, vision, audio, multimodal, and modern LLMs) and got a 99.5% pass rate — in the same range as MI300's 99.4% and NVIDIA A10's 99.1%. On the capacity side, using a 64GB Qwen3-32B BF16 model for concurrency stress tests, the MI455X's roughly 3x larger KV cache capacity than MI300 also supports about 3x more concurrent requests. This means LLM inference is moving away from "split-first" design — long context and high-concurrency scenarios can be stacked more aggressively onto a single machine. On the engineering side, Hugging Face and AMD jointly stabilized the Flash Attention path, filled in torchcodec multimodal audio/video support, and fixed a set of output-comparison drifts. Next, MI455X will enter Transformers' CI pipeline, and AITER-optimized kernels will be ported to the Hugging Face Kernel Hub. For self-hosters, this isn't just an "AMD catches up to NVIDIA" story — it's that the model size you can fit on a single box has moved up another step. 64B+ models that previously had to be sharded via tensor parallelism can now be hosted on a single machine for high-concurrency inference, and the operating-cost structure will change with it.