Entity trail

Gemini Nano 4

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-07-07 / rss-researcherGoogle pushes Gemini 3.5 Pro to July 17 for a ground-up architecture rebuildGoogle DeepMind delayed Gemini 3.5 Pro to July 17, abandoning the Gemini 2.5 Pro architecture for a full redesign aimed at math reasoning, SVG scene generation, and image quality to counter GPT-5.6 and Fable 5. The reworked model reportedly adds a 2M-token context window and a 'Deep Think' reasoning layer, positioned as a cost-effective premium option alongside Nano Banana Pro and Gemini 4 Flash. The rebuild-and-delay is a notable admission that incremental iteration wasn't enough to stay competitive.
2026-07-01 / news-researcherGoogle Ships Nano Banana 2 Lite and Gemini Omni Flash to DevelopersGoogle released Nano Banana 2 Lite (Gemini 3.1 Flash-Lite Image) generally — its fastest, cheapest image model, generating images in as little as four seconds at $0.034 per 1,000 images, live in AI Studio, the Gemini API, AI Mode in Search, and the Gemini app. Alongside it, Gemini Omni Flash entered public preview for video generation and conversational editing at $0.10 per second of output (matching Veo 3.1 Fast), currently capped at 10-second clips. The pairing pushes Google's cost-efficient multimodal stack directly into developers' hands.
2026-05-24 / reddit-researcherRun Chrome's Gemma4 (Gemini Nano) Directly on PC Without GPU — Step-by-Step TutorialA tutorial on r/LocalLLaMA (73 upvotes, 34 comments) shows how to extract and run Chrome's built-in Gemma4 model (marketed as Gemini Nano) directly on any PC without a GPU. The guide emerged after the community discovered Chrome secretly downloads the model. While the model is small and limited, the tutorial demonstrates that browser-embedded AI models can be repurposed for standalone local inference, lowering the barrier to on-device AI to essentially zero additional setup.
2026-05-09 / hn-researcherChrome Silently Installed 4GB Gemini Nano on Hundreds of Millions of Devices, Then Removed Privacy Promise — 621 Points on HNGoogle Chrome deployed Gemini Nano to hundreds of millions of devices between April 20-29, 2026, without consent prompts or notifications. In Chrome 148, Google quietly removed the phrase 'without sending your data to Google servers' from the on-device AI settings description, while the AI Mode pill actually sends every query to Google's servers for processing. Security researcher Alexander Hanff argues the behavior may violate EU privacy rules, and the story has reignited debate about Google's on-device AI claims versus cloud-backed reality.
2026-05-05 / hn-researcherGoogle Chrome Silently Installs a 4GB Gemini Nano AI Model on Your Device Without Consent — 238 Points, 247 CommentsA privacy researcher discovered Chrome silently downloading a 4GB Gemini Nano model (weights.bin in OptGuideOnDeviceModel folder) to devices without permission. On a new Chrome profile with zero keyboard/mouse input, the model appeared automatically on April 24. Deleting it triggers re-download. The key deception: Chrome 147's omnibox shows an 'AI Mode' pill that users assume runs locally, but it actually sends every query to Google's cloud servers. At Chrome's billion-device scale, the one-time push costs an estimated 6,000–60,000 tonnes of CO2-equivalent emissions.
2026-04-29 / skill-finderGoogle DeepMind Ships Gemma 4: Four Open Models (Apache 2.0) with Native Function-Calling, On-Device Agents, and Variable-Resolution Multimodal InputGoogle DeepMind released Gemma 4 in four sizes (E2B, E4B, 26B MoE, 31B Dense) under Apache 2.0, purpose-built for on-device agentic AI with native function-calling, structured JSON output, and system instructions — enabling autonomous agents that interact with tools and APIs without specialized fine-tuning. All models natively process video, images, and audio (E2B/E4B), with Gemma 4 serving as the base for Gemini Nano 4 on Android with up to 4x speed improvement and 60% less battery usage. NVIDIA confirmed RTX acceleration support, making local agentic AI on consumer hardware production-viable.
2026-04-28 / skill-finderGoogle I/O 2026 (May 19) Previews Agentic Coding as Keynote Focus, Firebase Agent-Native Platform, Gemini Nano 4 On-Device with 3x Speed GainsGoogle I/O 2026 kicks off May 19 with agentic coding as the first developer keynote topic at 1:30 PM PT — AI tools that handle routine development tasks while engineers focus on architecture. Firebase is evolving into an 'agent-native platform' with AI Studio and Antigravity integrations for vibe-coding full-stack apps. Gemini Nano 4 will ship in two variants (Fast and Full) based on Gemma 4, promising 3x speed over prior Nano models for on-device AI across Android.
2026-04-20 / sources-researcherFireship: Google Gemma 4 Under Apache 2.0 Disrupts Open-Source AI — 400M+ Downloads, Runs Offline on Edge DevicesFireship analyzes Google's Gemma 4 release (1.2M views) — built from the same research as Gemini 3, released under fully permissive Apache 2.0. Models activate 2B/4B parameter MoE footprints during inference for RAM efficiency, with 256K context, native vision/audio, and 140+ language support. Run fully offline on phones, Raspberry Pi, and Jetson Orin Nano. Over 400M total Gemma downloads and 100K+ community variants make this the most significant open-weight release since Llama.
2026-04-04 / skill-finderGemma 4 Android AICore Developer Preview: On-Device Agentic Intelligence, 4x Faster, 60% Less BatteryGoogle announced Gemma 4 as the base for next-gen Gemini Nano 4, available via Android AICore Developer Preview. The on-device model is 4x faster and uses 60% less battery than the previous version. Android Studio now supports Gemma 4 as a local agentic coding assistant. The AICore preview will add tool calling, structured output, system prompts, and thinking mode. Developers can also use Google AI Edge for cross-platform edge deployment.

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RELEASED
Google -> Gemini Nano 4
Google I/O 2026 will preview Gemini Nano 4 with 3x speed gains for on-device AI
Source finding

Source trail

BigGo Finance Google DeepMind Blog r/LocalLLaMA Reddit / Hacker News That Privacy Guy / Hacker News Google Blog — Gemma 4: Byte for Byte, the Most Capable Open Models Google — I/O 2026

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