Technology

Arm accelerates its on-device AI revolution with new edge computing innovations in 2025

Thursday, 6 November 2025 5:08AM UTC

Arm's latest innovations in 2025 are set to revolutionise edge AI, enabling smarter, private, and more responsive devices through advanced hardware and open-source software, transforming mobile, gaming, and embedded applications.

Arm is accelerating the move towards ubiquitous on-device artificial intelligence (AI) with a series of innovations unveiled in October 2025 that are set to redefine the landscape of edge intelligence. These developments cover a broad spectrum of applications—from gaming and neural graphics to embedded systems—illustrating a strategic emphasis on localising AI processing closer to users and data sources. The overarching goal is to enable more responsive, private, and efficient AI experiences without reliance on cloud connectivity, a shift that is poised to transform how intelligent experiences are created and delivered.

At the heart of this push is the general availability of ExecuTorch 1.0, an open-source inference engine co-developed with Meta. Designed to operate efficiently across Arm CPUs, GPUs, and NPUs, ExecuTorch leverages specialised hardware such as Scalable Matrix Extension 2 (SME2) for advanced matrix processing, Arm Neural Technology which scales inference, and the Ethos-U NPU family. This combination allows developers to deploy AI models with low latency and power consumption across a diverse array of edge devices—from minimalist microcontrollers to sophisticated smartphones. Industry experts highlight this as a critical milestone in making advanced AI accessible at the edge, significantly reducing dependence on cloud infrastructure while enhancing AI performance and privacy.

One of the most striking applications showcased is the capability to run large language models (LLMs) directly on smartphones, enhancing mobile gaming experiences with real-time conversational AI. In collaboration with Unreal Engine's Neural Network Engine and KleidiAI optimisations, Arm demonstrated this through the “Space Bartender” demo—a game featuring an interactive NPC powered by the Whisper voice model and a 4-bit quantised SmolLM2. This setup delivers a 2.3 times performance improvement while maintaining low power use, enabling network-free, immersive AI interactions on mobile devices. This breakthrough signals a paradigm shift for mobile gaming, where AI-driven characters can offer highly personalised and dynamic interactions entirely on-device, improving both user experience and data security.

Beyond conversational AI, Arm is driving innovation in visual computing and embedded intelligence through tools such as the Model Gym developer toolkit and the Arm Neural Graphics SDK. These enable developers to train and deploy neural graphics models like neural super-sampling (NSS) that enhance visual fidelity on mobile and embedded platforms, all while reducing computational and power costs. The Neural Graphics SDK includes Unreal Engine 5.4 integration for AI-powered rendering, promising near-console-level graphics efficiency on mobile devices. Such advancements empower game developers and device makers to deliver superior graphical performance in increasingly compact and energy-efficient ways.

The impact of these on-device AI innovations extends into real-world consumer products and specialised applications. For instance, the vivo X300 smartphone series incorporates SME2 technology to accelerate diverse AI workloads involving vision, speech, and text, demonstrating practical consumer integration. Meanwhile, Alif Semiconductor is advancing intelligent edge computing through embedded controllers powered by the Ethos-U85 NPU, enabling high-performance, low-power generative AI models tailored for smart homes, healthcare devices, and wearables. Even mobile photography benefits, with real-time neural-camera denoising technology on Arm-based devices using SME2, producing cleaner images and smoother 4K video in difficult low-light conditions, thus enhancing mobile camera capabilities.

Arm’s broad strategy integrates substantial software and hardware innovations supporting scalable AI performance at the edge. The integration of KleidiAI into ExecuTorch and other major AI frameworks such as Google's XNNPACK and MediaPipe further enhances performance without requiring developers to alter their codebases. Since 2024, KleidiAI has brought significant speed-ups and power efficiency gains to generative AI workloads on existing devices, including several-year-old smartphones and popular edge platforms like the Raspberry Pi 5. Coupled with advancements like SME2 and the Armv9 edge AI platform featuring the Cortex-A320 CPU and Ethos-U85 NPU, Arm’s ecosystem provides an 8-fold machine learning performance increase over previous generations, endorsed by industry leaders including AWS, Siemens, and Renesas.

This comprehensive on-device AI push underscores Arm’s foundational role in the next wave of intelligent computing. Through optimised hardware, open-source software, and tailored developer tools, Arm is not only enabling AI at the edge but making it practical and pervasive. The localisation of AI—from sophisticated language models to advanced neural graphics—promises enhanced user experiences, improved privacy, and a new range of possibilities across technology sectors. As AI moves decisively onto devices, Arm’s innovations lay critical groundwork for its widespread adoption and the future of edge intelligence.

📌 Reference Map:

^[1] (StartupHub) - Paragraphs 1, 2, 3, 4, 5, 6, 7
^[2] (Arm Newsroom) - Paragraphs 1, 2
^[3] (Arm Newsroom) - Paragraphs 5, 6
^[4] (Arm Newsroom) - Paragraph 6
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^[6] (Arm Newsroom) - Paragraph 3
^[7] (Arm Newsroom) - Paragraph 6

Source: Noah Wire Services

More on this

https://www.startuphub.ai/ai-news/ai-research/2025/arms-on-device-ai-push-redefines-edge-intelligence/ - Please view link - unable to able to access data
https://newsroom.arm.com/blog/top-12-innovations-from-arm-in-october-2025 - In October 2025, Arm unveiled significant advancements in on-device AI, including the general availability of ExecuTorch 1.0, an open-source inference engine co-developed with Meta. This engine is designed to run efficiently across Arm CPUs, GPUs, and NPUs, enabling developers to deliver low-latency, power-efficient AI directly on a wide range of edge devices. ExecuTorch leverages Arm's specialized hardware, such as Scalable Matrix Extension 2 (SME2) for matrix processing, Arm Neural Technology for scaling inference, and the Ethos-U NPU family, effectively democratizing advanced AI capabilities at the edge. This development marks a pivotal moment for Arm on-device AI, moving AI processing closer to the user and the data source, and enabling entirely new classes of applications that demand real-time responsiveness and data privacy, unburdened by cloud connectivity.
https://newsroom.arm.com/news/pytorch-kleidi-integrations-cloud-to-edge - Arm has integrated KleidiAI into ExecuTorch, the new on-device inference runtime from PyTorch, aiming to deliver immediate performance improvements for developers. This integration, completed in October 2024, promises exciting performance enhancements for edge devices across applications currently being production-tested or rolled out in ExecuTorch. KleidiAI has also been integrated with other major AI frameworks, including Google's XNNPACK and MediaPipe, and Tencent's Hunyuan large language model, demonstrating its impact on real-world workloads. As Kleidi continues to be integrated with both PyTorch and ExecuTorch releases, alongside all other major AI frameworks, developers will be able to immediately run efficient and performant AI workloads on Arm across a spectrum of devices, from cloud data centers to edge devices.
https://newsroom.arm.com/blog/august-2025-innovations-from-arm - In August 2025, Arm announced that ExecuTorch 0.7 now enables KleidiAI by default, delivering automatic acceleration on Arm CPUs with zero integration effort. This advancement makes generative AI performant on millions of existing devices, including 3–5-year-old smartphones and Raspberry Pi 5, thanks to Arm CPU features like SDOT and I8MM. On-device use cases such as private voice assistants, message summarization, and local code/gen AI copilots are now possible without relying on the cloud and without draining the battery. With Arm's recent SME2 announcement, the role of Arm KleidiAI is increasingly clear as Arm's AI accelerator layer powering the next wave of AI. By embedding into widely used Edge AI frameworks like XNNPack, MediaPipe, MNN, ONNX Runtime, and even llama.cpp, KleidiAI has delivered substantial performance improvements with no code changes required by developers.
https://newsroom.arm.com/blog/july-2025-innovations-from-arm - In July 2025, Arm's integration of SME2 and KleidiAI into XNNPack unlocked seamless AI acceleration for edge devices without changing a line of code. With support for Int4/Int8 matrix multiplication and dynamic quantization, developers saw over 30% performance gains in models like Gemma 2 and Stable Audio Open Small. Now enhanced by SME2 in Armv9 CPUs, this integration brings high-throughput efficiency to both convolutional and generative AI. It's a clear step toward Arm's vision of scalable, portable AI performance across the compute spectrum.
https://newsroom.arm.com/blog/tech-innovations-from-arm-in-march-2025 - In March 2025, Arm highlighted how Arm CPUs, GPUs, and NPUs support generative AI workloads on-device, enabling game developers to build intelligent, responsive content pipelines without relying on the cloud. This approach reduces latency and saves bandwidth, allowing for more efficient and effective AI integration in mobile gaming applications.
https://newsroom.arm.com/blog/state-of-silicon-devices-q1-2025-roundup - In Q1 2025, Arm introduced the first Armv9 edge AI platform, integrating the Cortex-A320 CPU and Ethos-U85 NPU, optimized for on-device AI with models exceeding one billion parameters. This platform delivers an 8× improvement in machine learning performance over Cortex-M85-based solutions and has gained industry support from AWS, Siemens, and Renesas. The Cortex-A320 brings advanced AI capabilities and developer benefits to IoT, extending the features of the Armv9 architecture to power-efficient devices, alongside comprehensive software support.

Noah Fact Check Pro

The draft above was created using the information available at the time the story first emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed below. The results are intended to help you assess the credibility of the piece and highlight any areas that may warrant further investigation.

Freshness check

Score: 9

Notes: The narrative presents recent developments from October 2025, including the general availability of ExecuTorch 1.0 and advancements in on-device AI for mobile gaming. These events are corroborated by official Arm announcements and industry news from late October 2025. ([newsroom.arm.com](https://newsroom.arm.com/blog/top-12-innovations-from-arm-in-october-2025?utm_source=openai))

Quotes check

Score: 8

Notes: The report includes direct quotes from Arm executives and technical details about the ExecuTorch 1.0 release and its features. These quotes are consistent with statements made in official Arm communications and industry analyses from October 2025. ([newsroom.arm.com](https://newsroom.arm.com/blog/top-12-innovations-from-arm-in-october-2025?utm_source=openai))

Source reliability

Score: 7

Notes: The narrative originates from StartupHub.ai, a platform known for aggregating AI-related news. While it compiles information from reputable sources, the platform itself is not a primary news outlet. The report references official Arm Newsroom releases and other credible industry sources, enhancing its reliability. ([newsroom.arm.com](https://newsroom.arm.com/blog/top-12-innovations-from-arm-in-october-2025?utm_source=openai))

Plausability check

Score: 9

Notes: The claims about Arm's advancements in on-device AI, including the ExecuTorch 1.0 release and its applications in mobile gaming, align with recent industry trends and Arm's strategic focus on edge intelligence. The technical details provided are consistent with known capabilities of Arm's hardware and software platforms. ([newsroom.arm.com](https://newsroom.arm.com/blog/top-12-innovations-from-arm-in-october-2025?utm_source=openai))

Overall assessment

Verdict (FAIL, OPEN, PASS): PASS

Confidence (LOW, MEDIUM, HIGH): HIGH

Summary: The narrative accurately reflects recent developments in Arm's on-device AI initiatives, supported by official announcements and industry reports from October 2025. The information is current, consistent with known facts, and sourced from reputable entities, indicating a high level of credibility.

Artificial Intelligence
Edge Computing
Mobile Technology