Google has officially unveiled Gemini Intelligence, its most advanced suite of AI features for Android, during the I/O edition of The Android Show. The rollout is slated to begin this summer, but the company has also disclosed stringent hardware requirements that will limit availability to only the most premium devices. According to the official specifications, phones must meet or exceed 12GB of RAM, feature a flagship-class system-on-chip (SoC), and support both AI Core and Gemini Nano version 3 or higher. These demands effectively exclude the vast majority of current Android smartphones, including many popular models from the past few years.

What Is Gemini Intelligence?

Gemini Intelligence is an umbrella term encompassing a collection of AI-powered features designed to enhance user experiences across the Android ecosystem. Notable examples include Gboard's new voice-to-text feature called “Rambler,” which promises more natural and accurate dictation; an upgraded Chrome auto-fill that can handle complex multi-field forms such as insurance applications or tax documents; and a generative widget creation tool called “Create My Widget.” These capabilities rely on powerful on-device inference, leveraging the latest neural processing units (NPUs) to perform tasks locally without sending data to the cloud. Google has emphasized privacy and speed as key advantages of this approach.

The integration of Gemini Intelligence represents a significant generational leap over earlier AI offerings. Previous iterations, like Google Assistant and early versions of Gemini, operated largely through cloud servers. While cloud-based AI remains essential for some tasks, local processing allows for near-instantaneous responses and works offline. The shift toward on-device AI aligns with broader industry trends, with Apple, Samsung, and Qualcomm all investing heavily in edge computing.

The Hardware Requirements in Detail

The primary bottleneck is the 12GB RAM requirement. Most mid-range and older flagship phones ship with 8GB or less. Even the Pixel 9 series, which launched in 2024, maxes out at 8GB for the base model and 12GB only for the Pro variant. However, the requirement also stipulates compatibility with AI Core, a new system service that manages AI model execution, and Gemini Nano v3, the latest version of Google's on-device language model. Google's developer documentation lists devices that support Nano v3, and the list is short: essentially only 2026 flagship models from brands like Google, OPPO, and a few others. This means devices like the Pixel 7 Pro (12GB), Pixel 8 Pro (12GB), and even the Pixel 9 Pro (12GB) are not on the list because they do not support Nano v3. Similarly, Samsung's Galaxy Z Fold 7 and TriFold, despite having 12GB of RAM, lack the necessary software stack or chipset compatibility.

The chipset requirement is equally restrictive. Qualcomm's Snapdragon 8 Elite Gen 4 and the upcoming Tensor G5 are expected to be among the first to meet the performance thresholds. MediaTek's Dimensity 9400 may also be supported, but Google has not released a comprehensive list. The need for “flagship chip” implies that only the most cutting-edge processors with dedicated AI blocks (NPUs, Hexagon DSPs) will make the cut.

Phones That Are Excluded

Based on the announced criteria, the following popular devices are confirmed as ineligible for Gemini Intelligence:

• Pixel 7 Series: The Pixel 7 and 7 Pro have 8GB and 12GB of RAM respectively, but the Tensor G2 chipset does not meet the Nano v3 requirements.
• Pixel 8 Series: The Pixel 8 and 8 Pro feature Tensor G3, but again, no Nano v3 support.
• Pixel 9 Series: Despite having Tensor G4 and up to 12GB RAM, the series is not on the supported list.
• Samsung Galaxy S24 Series: Even the top-tier S24 Ultra with 12GB RAM lacks the necessary software and updated NPU driver.
• Galaxy Z Fold 7 and TriFold: Samsung's 2025 foldables have sufficient RAM but are not certified for Nano v3.
• OnePlus 12 and 13: Despite flagship specs, early tests show they do not pass AI Core validation.

Only devices released in 2026, such as the Pixel 10 series, OPPO Find X9 series, and possibly the Xiaomi 16 series, have been confirmed to support Gemini Intelligence. This limited rollout is reminiscent of the initial launch of Google Assistant on the Pixel 2, which received exclusive features for a period.

Why Such High Requirements?

Google's decision to gate Gemini Intelligence behind premium hardware stems from the computational demands of modern large language models (LLMs). Local inference of models with billions of parameters requires substantial RAM to store model weights and intermediate data. Additionally, the NPU must support bfloat16 or int8 quantization for efficient operation. The requirement also likely aims to ensure a consistent user experience across devices, avoiding performance issues or crashes. By limiting availability, Google can fine-tune the software stack for a small set of guaranteed-capable hardware.

Another factor is strategic market segmentation. Google is positioning Gemini Intelligence as a differentiator for the most premium segment of the Android market, encouraging users to upgrade to 2026 flagships. This approach also gives chipmakers like Qualcomm and MediaTek a clear target for future NPU development.

The timing of the announcement—early 2026—suggests that Google expects the majority of devices shipping in the second half of the year to meet the criteria. For example, the Pixel 10, expected in October 2026, will be among the first beneficiaries. Meanwhile, consumers who purchased a high-end phone in 2024 or 2025 may be surprised to learn that their device is already obsolete in terms of AI capabilities.

Comparison with Competing Ecosystems

Apple's approach with Apple Intelligence is similarly restrictive, requiring at least the A17 Pro or M1 chips and 8GB of RAM. However, Google's 12GB RAM and specific Nano version requirement is even more stringent. Samsung's Galaxy AI, launched with the S24 series, uses cloud-based processing for many features, though some on-device tasks run on the Snapdragon 8 Gen 3. Qualcomm is working on its own AI Engine to standardize features across Android devices, but Google's control over the Android ecosystem gives it the final say.

The exclusion of foldable devices is particularly noteworthy. The Galaxy Z Fold 7, released in 2025, is a $1,800 device with 12GB of RAM but lacks the necessary AI stack. This sends a confusing signal to premium buyers: the most expensive Android phones may not get the latest AI features. Google's decision may stem from the fact that foldables often use slightly older chipsets to meet thermal and space constraints, and their custom cooling solutions may not sustain prolonged AI workloads.

How to Check if Your Phone Supports Gemini Intelligence

Google plans to roll out a compatibility checker in the Play Store later this spring. Users can also check the official developer documentation for Gemini Nano v3 support. However, the list is dynamic and may grow as more devices receive updates. For now, only devices with a 2026 flagship chipset and at least 12GB of RAM can run AI Core v2.1+ and Gemini Nano v3. Some manufacturers, like OPPO and Xiaomi, have confirmed future updates for their 2025 flagships, but Google has not committed to any retroactive support.

In summary, Gemini Intelligence represents a monumental step forward for on-device AI on Android, but its availability is strictly limited. Users eager to experience features like Rambler voice typing or advanced auto-fill should plan to purchase a 2026 flagship. The rest of the Android ecosystem will have to wait or rely on cloud-based alternatives.

Source: Android Authority News