Because I unable to find any info about this so I asked Gemini Flash Extended to explain me - please confirm me if it is correct:

1. The Core LLM: Gemini Nano v3

For system-wide text, multimodal parsing, and proactive OS features (like Magic Cue, Call Notes, and local scam detection), the Pixel 10 Pro utilizes Gemini Nano v3.

Local AI Master

While Google has kept the exact, combined parameter count for the v3 architecture under wraps, it is a highly optimized, fully multimodal upgrade from the older 1.8B. This new version requires a steep hardware baseline across the Android ecosystem—specifically demanding a flagship chip and a minimum of 12GB of system RAM just to run.

9to5Google

2. The Imaging Model: 1-Billion-Parameter Diffusion Model

Exclusive to the Pixel 10 Pro and Pro XL models is a dedicated 1-billion-parameter image diffusion model that runs entirely locally.

Wikipedia

This model is assigned to a single, heavy task: powering the 100x Pro Res Zoom feature. When you zoom past optical limits, this specific model leverages the Tensor G5’s upgraded TPU to artificially upscale and reconstruct the fine details of the image on the fly, saving both the raw version and the AI-enhanced photograph locally.

Wikipedia

n paper, a 20-billion-parameter model sounds like it would completely blow the Pixel 10 Pro out of the water. However, the reality is a lot closer—and more interesting—because of a clever architectural trick Apple is pulling off.

It comes down to a classic tech matchup: Apple’s sparse flexibility vs. Google’s dense efficiency.

Apple's Trick: The "Mixture of Experts" (MoE)

When Apple announced the AFM 3 Core Advanced model at WWDC, the headline was "20 billion parameters," but the fine print revealed how it actually works.

The iPhone 17 Pro doesn't actually run a massive 20B model in its RAM all at once. Doing that would instantly choke the battery and memory. Instead, it uses a sparse architecture.

• The Storage Pool: The full 20-billion-parameter model lives on your iPhone’s fast flash storage (NAND).
• The Active Slice: When you ask Siri a question, an orchestrator instantly figures out what kind of task it is and pulls only the relevant "expert" sub-models into the active memory (DRAM).
• The Reality: At any single moment during a query, the iPhone 17 Pro is only activating 1 to 4 billion parameters.

So while the iPhone has a much larger "library" of total knowledge to swap in and out, the actual brainpower it applies to a single word is roughly the size of a standard mobile model.

Google's Approach: Blazing-Fast Density

Google took the opposite route with Gemini Nano v3 on the Pixel 10 Pro. Instead of swapping pieces in and out of storage, Gemini Nano v3 is a highly distilled, dense model that lives entirely in the Pixel's massive 16GB of RAM.

Because it is permanently sitting in memory and custom-tailored to the Tensor G5’s TPU, it operates with insane efficiency. For raw processing, Nano v3 can hit text speeds near 940 tokens per second. Furthermore, Google’s architecture is natively multimodal from the ground up, meaning it handles text, images, and audio natively in a single layout rather than routing tasks to separate specialized experts.

The Real-World Difference: Which is Better?

Instead of one being universally "much better," they are optimized for entirely different user experiences:

Feature	iPhone 17 Pro (AFM 3 Core Advanced)	Pixel 10 Pro (Gemini Nano v3)
Edge Case Knowledge	Winner. The 20B total size gives Apple a wider vocabulary and better handling of niche topics.	Good, but heavily distilled to keep the file size small enough for RAM.
Speed & Latency	Variable. Tends to have a microscopic delay when swapping "experts" from storage to RAM.	Winner. Blisteringly fast response times because everything sits natively in RAM.
System Integration	Focused heavily on deep voice expressiveness and structural text cleanup.	Deeply integrated into the OS for live audio scanning, proactive assistance (Magic Cue), and local scam detection.

The Bottom Line: Don't let the "20 Billion" number fool you into thinking the iPhone 17 Pro has a server-grade brain inside it. Apple's model will likely feel smarter when it comes to nuanced writing tone and complex voice commands, but the Pixel 10 Pro's Gemini Nano v3 will still hold the crown for pure on-device speed and deeply integrated system actions.