# Mobile Systems

Published articles for Mobile Systems.

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## Accelerating Gemini Nano models on Pixel with frozen Multi-Token Prediction

DevFeed: [Accelerating Gemini Nano models on Pixel with frozen Multi-Token Prediction](<https://devfeed.tech/articles/accelerating-gemini-nano-models-on-pixel-with-frozen-multi-token-prediction-6744.md>)

Original publisher: [Read original article](<https://research.google/blog/accelerating-gemini-nano-models-on-pixel-with-frozen-multi-token-prediction/>)

Published: 2026-06-26T18:30:00Z

Content type: article

Language: en

Sources: [The latest research from Google](<https://devfeed.tech/sources/the-latest-research-from-google.md>)

Topics: [AI Inference](<https://devfeed.tech/topics/ai-inference.md>), [On-device AI](<https://devfeed.tech/topics/on-device-ai.md>), [Google](<https://devfeed.tech/topics/google.md>), [LLMs](<https://devfeed.tech/topics/llms.md>), [gemma](<https://devfeed.tech/topics/gemma.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [energy](<https://devfeed.tech/tags/energy.md>), [gemini](<https://devfeed.tech/tags/gemini.md>), [inference](<https://devfeed.tech/tags/inference.md>), [machine-intelligence](<https://devfeed.tech/tags/machine-intelligence.md>), [mobile-systems](<https://devfeed.tech/tags/mobile-systems.md>), [natural-language-processing](<https://devfeed.tech/tags/natural-language-processing.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [on-device-ai](<https://devfeed.tech/tags/on-device-ai.md>), [phones](<https://devfeed.tech/tags/phones.md>)

### AI overview

Google Research describes a method for retrofitting Multi-Token Prediction onto frozen Gemini Nano v3 production models to accelerate on-device inference on Pixel phones. The approach targets mobile energy and memory constraints, improving the speed and energy efficiency of features such as notification summaries and proofreading without requiring separate drafting models.

### Source excerpt

Machine Intelligence

## Small models, big results: Achieving superior intent extraction through decomposition

DevFeed: [Small models, big results: Achieving superior intent extraction through decomposition](<https://devfeed.tech/articles/small-models-big-results-achieving-superior-intent-extraction-through-decomposition-6874.md>)

Original publisher: [Read original article](<https://research.google/blog/small-models-big-results-achieving-superior-intent-extraction-through-decomposition/>)

Published: 2026-01-22T16:56:44Z

Content type: article

Language: en

Sources: [The latest research from Google](<https://devfeed.tech/sources/the-latest-research-from-google.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [multimodal](<https://devfeed.tech/topics/multimodal.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Google](<https://devfeed.tech/topics/google.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [generative](<https://devfeed.tech/tags/generative.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [inference](<https://devfeed.tech/tags/inference.md>), [llms](<https://devfeed.tech/tags/llms.md>), [machine-perception](<https://devfeed.tech/tags/machine-perception.md>), [mobile](<https://devfeed.tech/tags/mobile.md>), [mobile-systems](<https://devfeed.tech/tags/mobile-systems.md>), [models](<https://devfeed.tech/tags/models.md>), [multimodal](<https://devfeed.tech/tags/multimodal.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [performance](<https://devfeed.tech/tags/performance.md>)

### AI overview

Google researchers describe a decomposed approach for extracting user intent from web and mobile UI interaction trajectories with small multimodal language models. The method summarizes individual screens first, then infers overall intent from the sequence of summaries, achieving results comparable to much larger models while supporting on-device processing.

### Source excerpt

Generative AI

## Toward provably private insights into AI use

DevFeed: [Toward provably private insights into AI use](<https://devfeed.tech/articles/toward-provably-private-insights-into-ai-use-6904.md>)

Original publisher: [Read original article](<https://research.google/blog/toward-provably-private-insights-into-ai-use/>)

Published: 2025-10-30T10:56:00Z

Content type: article

Language: en

Sources: [The latest research from Google](<https://devfeed.tech/sources/the-latest-research-from-google.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Generative AI](<https://devfeed.tech/topics/generative-ai.md>), [Confidential Computing](<https://devfeed.tech/topics/confidential-computing.md>), [Google](<https://devfeed.tech/topics/google.md>), [trusted-execution-environment](<https://devfeed.tech/topics/trusted-execution-environment.md>), [data-processing](<https://devfeed.tech/topics/data-processing.md>), [Large language models (LLMs)](<https://devfeed.tech/topics/large-language-models-llms.md>), [gemma](<https://devfeed.tech/topics/gemma.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [confidential-computing](<https://devfeed.tech/tags/confidential-computing.md>), [data-processing](<https://devfeed.tech/tags/data-processing.md>), [gemma](<https://devfeed.tech/tags/gemma.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [google](<https://devfeed.tech/tags/google.md>), [large-language-models-llms](<https://devfeed.tech/tags/large-language-models-llms.md>), [mobile-systems](<https://devfeed.tech/tags/mobile-systems.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [research](<https://devfeed.tech/tags/research.md>), [security-privacy-and-abuse-prevention](<https://devfeed.tech/tags/security-privacy-and-abuse-prevention.md>), [software-systems-engineering](<https://devfeed.tech/tags/software-systems-engineering.md>)

### AI overview

Google Research introduces provably private insights, a system that combines large language models, differential privacy, and trusted execution environments to analyze aggregate patterns in on-device generative AI use without exposing individual data.

### Source excerpt

Generative AI