Arm has unveiled Performix, a free performance analysis toolkit to help developers and AI agents in scaling efficient AI experiences across Arm-based compute platforms.
Performix collects runtime data directly from Arm silicon, transforming low-level hardware metrics such as memory bandwidth, latency, cache efficiency, and CPU utilisation into actionable insights.
The toolkit integrates seamlessly into modern workflows, including tools like GitHub Copilot and Gemini via Arm MCP Server to enable continuous optimisation for complex agentic AI workloads.
Building on more than 1.25 billion Arm Neoverse cores shipped and the recent Arm AGI CPU launch, Performix extends Arm’s performance leadership into software stacks amid surging agentic AI demands.
Major players have provided feedback and are already using Performix to simplify migrations from x86 and boost developer velocity.
“As developers and cloud architects increasingly seek to move existing x86 cloud workloads onto Arm, they need clear metrics and insights to help them identify performance bottlenecks efficiently. Arm Performix was developed with extensive feedback from our team to help simplify this migration,” said Pat Stemen, Vice President of Azure Hardware Systems and Infrastructure at Microsoft.
“The tool is approachable, and quick to set up and run. Using the actionable insights Performix generated, we found a clear path to achieving a 10 percent performance boost on one of our key workloads in just a few days. The tool has been a big win for developer velocity in our performance tuning process,” said Jawwad Asghar, Senior Software Engineer of MongoDB.
According to Alex Spinelli, SVP of AI and Developer Platforms at Arm, Performix unlocks the full potential of the Arm platform through highly accessible, deep performance insights, so developers spend less time interpreting data and more time optimizing where it matters.
“This marks yet another significant step in Arm’s long-standing commitment to our ecosystem, with Performix empowering developers to build, optimise and scale the next generation of cloud and AI infrastructure on Arm,” he wrote in a blogpost.
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