AMD has released AMD ROCm 10, making the AI-native software experience ROCm.AI that is designed to accelerate development velocity and performance optimisation on AMD hardware, generally available for users.
ROCm.AI brings together three core developer experiences: AMD Skills, the ROCm CLI and AMD Hyperloom. Together, they introduce AMD expertise and agentic workflows into the tools developers already use, enabling innovation to evolve at the pace of AI.
Through AI-driven optimisation of kernels, memory management and scheduling, a system configured with ROCm.AI delivers an average 3,3x inference improvement and 2,4x training improvement over ROCm 7 on the same hardware.
ROCm.AI supports developers across three parts of the AI development process: optimizing inference performance, building with AMD expertise and running AI workloads.
ROCm Hyperloom, a key component of ROCm.AI, is an autonomous agentic system for optimizing end-to-end inference workloads across host code and GPU kernels.
Hyperloom profiles workloads, identifies bottlenecks, explores optimization options, implements targeted changes, benchmarks the results, and validates performance and correctness.
With ROCm 10, Hyperloom expands support across AMD Instinct™ GPUs, with support for vLLM and SGLang. Developers can target optimizations across HIP, Triton and FlyDSL, with reports describing proposed code changes and measured or expected performance improvements.
Hyperloom is available through standalone workflows and AMD Skills, giving developers multiple ways to incorporate agentic optimization into their development process.
AMD Skills brings curated AMD knowledge and validated workflows into supported AI coding agents like Claude Code, Cursor and Codex, giving developers AMD-specific guidance within the tools they already use. With ROCm 10, the AMD Skills catalog expands across three areas:
- Client-native workflows for local AI and application integration.
- Cross-stack workflows for diagnostics, routing, replay analysis and optimization.
- Server-native workflows for AMD Instinct GPUs and AMD EPYC™ processors, including serving, profiling and performance analysis.
The skills previewed at Advancing AI are now available through the Claude Code, Codex and Cursor marketplaces, as well as through the open catalog on GitHub. Each shipped skill passes structural and behavioral testing before release to help provide consistent, reliable workflows.
The ROCm CLI, a Technology Preview component of ROCm.AI, provides a stable, unified command-line interface for setting up, managing and operating AI workloads on AMD hardware.
Developers can use the same workflows manually, through an AI coding agent or in continuous integration (CI) environments. From a single interface, they can inspect systems, install and manage ROCm environments, serve models, run diagnostics, update components, and control runtimes.
The CLI is available on Windows as well as Linux as a prebuilt binary and does not require an existing ROCm installation. It delivers managed ROCm environments, supports multiple side-by-side runtimes including runtime activation and rollback, as well as integrated model serving and engine management. Adapters today support Lemonade on select AMD client systems and vLLM for AMD Instinct GPU serving.
The ROCm Console (formerly “dash”), included with the CLI, provides a real-time view of system status and workload activity. Developers can monitor ROCm runtime health, model serving, GPU utilization and benchmark telemetry, including metrics such as high bandwidth memory (HBM) usage, power consumption and tokens per watt on supported AMD Instinct systems.
Available as a Technology Preview, ROCm CLI provides a version-agnostic experience across ROCm releases, beginning with ROCm 7.13 software, with ROCm 10 official support coming soon.