Earlier this week, Google aired the highly anticipated I/O edition of The Android Show. The company teased that this would be one of the biggest years for the platform, and it delivered with the announcement of Gemini Intelligence. The rollout of Gemini Intelligence to Android phones is scheduled to start this summer. However, its list of demanding requirements means it will only be available for the most advanced devices.

Gemini Intelligence is an umbrella term that refers to Google’s most advanced AI features. Some examples include Gboard’s new voice-to-text “Rambler” feature; an enhanced version of Chrome auto-fill, which can handle more complicated forms; and Create My Widget. These features rely heavily on on-device AI processing to provide fast, privacy-conscious experiences without needing constant cloud connectivity. The underlying technology hinges on neural processing units (NPUs) and advanced chipsets that can efficiently run large language models locally.

System Requirements Behind the Hype

According to the footnotes on the Gemini Intelligence landing page, users will need at least 12GB of RAM. This requirement alone eliminates most older Pixel phones, including the Pixel 7 Pro, Pixel 8 Pro, and surprisingly even the Pixel 9 series and Google’s latest foldables. The Pixel 9 series, which launched in late 2024, ships with 12GB of RAM, yet Google’s own list suggests these devices do not meet the full criteria. Why? Because RAM is only part of the picture.

The requirements also mandate support for AI Core and Gemini Nano v3 or higher. AI Core is Google’s specialized runtime for on-device AI, and Gemini Nano is the smallest version of Google’s Gemini model, designed to run directly on smartphones. Version 3 (Nano v3) includes significant improvements in performance, accuracy, and the ability to handle multimodal inputs. As Android Authority contributor AssembleDebug points out, Google maintains a developer page listing which devices support Nano v3. Most of those devices were released in 2026, with the Pixel 10 series and OPPO Find X9 series being notable exceptions that support the older version. This means the Pixel 7 Pro, Pixel 8 Pro, and even the Pixel 9 series all miss out on Gemini Intelligence. Samsung’s Galaxy Z Fold 7 and TriFold also appear to be unsupported.

What This Means for the Android Ecosystem

The decision to set such high requirements is a double-edged sword for Google. On one hand, it ensures that only the most powerful hardware can deliver a smooth, reliable experience with advanced AI features. On the other hand, it creates a fragmentation issue, as many users who bought high-end phones in the past two years will be left out. This could potentially slow adoption of Gemini Intelligence, which competes with features from Apple Intelligence that are available on a wider range of iPhones.

Historically, Google has used its Pixel line as a testbed for new AI capabilities, gradually rolling them out to older models through future updates. However, with Gemini Intelligence, the onboard hardware requirements are so steep that even the Pixel 9 series—one of the most Pixel lineup's most powerful devices—does not qualify. This suggests that future flagship devices will need to be even more powerful, possibly with 16GB or 24GB of RAM as standard.

For Android manufacturers, this creates a new challenge. They must now balance cost against the need to equip devices with the necessary hardware to support Google’s latest AI initiatives. Budget and mid-range phones will likely remain incompatible for the foreseeable future, widening the gap between premium and budget segments. Smaller OEMs that lack the scale to produce high-end chipsets may struggle to keep up with the requirements.

Background on AI Core and Gemini Nano

AI Core was introduced by Google as part of Android’s neural networking stack. It provides a uniform API for developers to access on-device AI accelerators such as NPUs, DSPs, and GPUs. The goal is to make it easier to build apps that leverage machine learning without worrying about underlying hardware differences. Gemini Nano represents Google’s most compact large language model, optimized for mobile deployment. It can summarize text, generate responses, and perform other tasks directly on the device, reducing latency and protecting user privacy. Version 3 brings improvements in understanding context and handling multiple input types, which are essential for features like the Rambler voice-to-text and advanced form auto-fill.

The Gemini Nano v3 requirement is particularly stringent because it relies on specific hardware acceleration that older chipsets do not support. Even some phones with sufficient RAM, like the Galaxy Z Fold 7, lack the necessary NPU capabilities to run Nano v3 efficiently. This explains why Google’s list of supported devices is relatively short and dominated by 2026 flagships.

Impact on Users and Developers

For users, the main takeaway is that they may need to upgrade to a future flagship to experience the best of Google’s AI. The Pixel 10 series, expected later this year, is likely to be the baseline for Gemini Intelligence. Meanwhile, users of older devices will have to settle for more basic AI features or rely on cloud-based alternatives. This could lead to frustration, especially among Pixel enthusiasts who expect timely feature parity.

Developers face a tricky decision. They can build apps that use the Gemini Intelligence API, but they will have to ensure backward compatibility for devices that lack the required hardware. Google is encouraging developers to adopt the AI Core framework, but until a critical mass of compatible devices exists, many may choose to limit their AI features to cloud processing, which is less efficient and less private.

Another consideration is the role of Android updates. Google has historically provided long-term support for its Pixel phones, but the inability to support Gemini Intelligence on the Pixel 9 series raises questions about how long we should expect flagship phones to stay relevant for cutting-edge features. If AI requirements jump this dramatically, phones may become obsolete faster, both in terms of hardware and software capabilities.

Google’s decision also puts pressure on Qualcomm and MediaTek to produce chipsets that meet these requirements. The Snapdragon 8 Gen 4 or similar flagship processors will need to include powerful NPUs that can run Nano v3 or higher. Apple has already set a precedent with its Neural Engine, and Android OEMs must now catch up.

Ultimately, Gemini Intelligence represents a major step forward for on-device AI on Android, but its high entry barrier means that most users will not experience it anytime soon. Google is betting that the premium smartphone market will adopt these features quickly, driving hardware upgrades and consolidation around a few high-end platforms. However, the risk is that this strategy could alienate a large portion of the Android user base, particularly in emerging markets where cost-sensitive buyers dominate.

As the summer rollout approaches, we will likely see more clarity on which exact devices support Gemini Intelligence and whether Google plans to relax the requirements over time. For now, if you want the full AI experience, you may need to plan for a significant upgrade.

Source: Android Authority News