Is the AI ​​chip dead? What the new Arm processors mean for your next Android phone

Conversations about mobile AI are dominated by talk of NPUs, TPUs, and specialized neural accelerators. But what if your phone’s all-in-one processor could take on that burden instead? Arm is betting big on just that with its new C2-Ultra, a powerful architecture that will define the next generation of 2027 flagships, from the latest MediaTek and Samsung processors to perhaps future Google Tensor chipsets.

The twist of the hand here is interesting, if that’s the right word. Shifting the focus from simply increasing clock speeds and pipeline widths to accelerating more specialized use cases has potentially significant benefits if these workloads persist. However, there is no guarantee that the market will not continue to demand higher and higher peak overall performance, especially as mobile and PC use cases continue to clash.

So let’s dive into this year’s C2-Ultra, -Premium, -Pro and -Nano CPU cores to see what this revised strategy entails.

Arm’s biggest processor announcement this year is the C2-Ultra, the powerful successor to last year’s C1-Ultra. While Arm doesn’t confirm partner products in advance, the usual frequency of chip releases means this new core will likely head to Samsung’s next-gen Exynos and MediaTek Dimensity chipsets for phones around 2027. We might even see it in the next generation Google Tensor G7 if we’re lucky.

As for the core numbers, Arm says peak core performance is increased by 15% compared to its predecessor. However, increasing the clock speed to a fairly high 4.45 GHz provides an 8% performance improvement, so only the remaining 7% comes from core architecture improvements. Perhaps more importantly, the core can deliver the same performance as last year’s model while reducing power consumption by 38%, thanks in large part to the move to a 2nm process. C2-Ultra can now have up to 3MB of L2 cache, a useful performance boost for processors looking to trade silicon for memory.

Interestingly, and perhaps a little unusual for Arm, the C2-Ultra pipeline is the same width as the C1-Ultra. Improved performance does not come from doing more work per clock cycle. Instead, Arm increased the C2-Ultra’s execution window by 30%, which means about 2,600 instructions are executed simultaneously, compared to 2,000 in the C1-Ultra. Likewise, Arm has strengthened its out-of-order execution engines with smarter guesses and faster recovery, allowing code dependencies to be discovered and executed earlier by analyzing workload and data types.

The general idea is that C2-Ultra spends less time waiting for data and, where possible, selects important code to run in the optimal order. Removing these bottlenecks speeds up execution slightly and reduces power consumption by reducing the time spent moving data between caches.

Unfortunately, the C2-Premium, C2-Pro and C2-Nano did not receive such large-scale updates. They essentially have the same basic architecture as last year’s C1 variants, but with tweaked area, efficiency, and power on next-gen 2nm production lines.

No 2026 announcement is complete without artificial intelligence, and the announcement of the Arm C2 processor is no exception. In addition to the overall 15% performance boost, Arm boasts its next-generation processor configuration that can deliver up to 1.7x performance improvements for AI models by further accelerating low-precision calculations and using lookup table instructions (LUTi) to reduce memory bandwidth requirements.

This is achieved by placing two Scalable Matrix Extensions (SME2) modules on a shared CPU cluster instead of the single module that was supported last year. However, the new Xiaomi XRING O3 supports two SME2 devices with last year’s C1 architecture, so this does not seem to be a hard and fast rule.

In any case, the important feature of SME2 is that its code runs as part of the CPU’s normal instruction pipeline. This means that supporting enhanced AI acceleration on supported processors does not require any additional software developer work other than ensuring instructions are compiled into code. However, moving up to two SME2 blocks does not immediately double the throughput. Instead, the units operate in parallel, providing improved performance in scenarios where AI workloads can be shared. It’s not a free lunch, but the Arm reference platform also suggests that higher SME2 clock speeds are achievable this year (up to 3GHz, up from 2GHz), so it’s clear that AI workloads will benefit the most in this next generation.

In real-world use cases, Arm estimates a 40% reduction in speech latency in text, delivering near-instant voice recognition. Memory retrieval latency is now 41% faster, allowing the system to recall user preferences and past interactions with minimal latency. Finally, hint generation speed is increased by 25% in terms of time to first token, making on-device machine learning models more responsive.

As is always the case with Armagh’s statements, the main parts are simply stated here; their semiconductor partners must combine them into complete configurations. Presentation slides: Reference designs range from 2x C2-Pro/4x C2-Nano configurations for budget devices to 2x C2-Ultra and 6x C2-Pro for flagship-level products, with peak clock speeds of 4.45 GHz for the largest cores and 3.6 GHz for Pro cores. Obviously, the exact configurations, clock speeds, cache, SME2 and other configuration options vary by vendor.

If 2025/2026 products are anything to go by, we’re sure to see one or two of the largest C2-Ultra cores used to deliver reliable peak performance, coupled with C2-Premium and C2-Pro cores for sustained and multi-tasking workloads, and an SME2 block (or two) on ultra-premium chips for AI acceleration.

Arm notes that we should expect a 10-12 core processor configuration from at least one of its partners later this year, presumably the MediaTek Dimensity 9600. Stay tuned for more partner announcements as we get closer to 2027.