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Google DeepMind releases Gemini 4 Argon

On October 23, 2026, Google DeepMind released the frontier model Gemini 4 Argon. Google's official blog stated that the model performs outstandingly on complex tasks such as coding, mathematics, and 3D world building, and surpasses other frontier models on benchmarks across multiple domains; the company also showcased five community creative projects, including a 3D Earth that maps wildfires and seismic waves in real time, a turbofan engine simulation with live data, a 3D horse-drawn carriage generated from a single image, and a multiplayer capture-the-flag browser game, and said the model had already been made broadly available last week. On the same day, another report stated that Argon can learn physical tasks by watching videos and transfer them to Apptronik's Apollo humanoid robot, with Apollo hitting seven consecutive shots in internal tests; the report also said Argon scored 87% on the embodied reasoning benchmark ERQA. On October 24, the Gemini for Android app pushed a redesign of its sidebar and settings interface via a server-side update, and reports said the redesign had already arrived on iOS, macOS, and Web alongside Gemini 4 Argon last week.

Google DeepMind releases Gemini 4 Argon

On October 23, 2026, Google DeepMind released the frontier model Gemini 4 Argon. Google's official blog stated that the model performs outstandingly on complex tasks such as coding, mathematics, and 3D world building, and surpasses other frontier models on benchmarks across multiple domains; the company also showcased five community creative projects, including a 3D Earth that maps wildfires and seismic waves in real time, a turbofan engine simulation with live data, a 3D horse-drawn carriage generated from a single image, and a multiplayer capture-the-flag browser game, and said the model had already been made broadly available last week. On the same day, another report stated that Argon can learn physical tasks by watching videos and transfer them to Apptronik's Apollo humanoid robot, with Apollo hitting seven consecutive shots in internal tests; the report also said Argon scored 87% on the embodied reasoning benchmark ERQA. On October 24, the Gemini for Android app pushed a redesign of its sidebar and settings interface via a server-side update, and reports said the redesign had already arrived on iOS, macOS, and Web alongside Gemini 4 Argon last week.

View story:Google DeepMind releases Gemini 4 Argon

Google releases Gemini 4 Argon model

On October 13, 2026, Gemini 4 Argon appeared on the GCP quota page. Testing Catalog, citing AiBattle, said the model was expected to launch within a few hours and called it a precursor to an imminent API model release; earlier that day, a Google employee had also teased an upcoming release. That evening, Testing Catalog reported that the model had begun rolling out and was already live in GCP's Agent Studio, where users could test it, with Google AI Studio and the Gemini app expected to follow. On October 14, Google officially released Gemini 4 Argon, open to developers and enterprises worldwide, usable via AI Studio and the Gemini platform API, and supported in Google Antigravity as well as the Gemini app and Search AI Mode for Ultra and Pro subscribers; reports said it supports long decoding output of up to 1,048,576 tokens and announced limited-time introductory pricing.

View story:Gemini 4 Argon appears on the GCP quota page

Google opens Gemini 4 Argon to developers

On October 13, 2026, Google announced that developers can now use Gemini 4 Argon to build applications. This frontier model targets complex workflows such as real software engineering, enterprise knowledge work, and cybersecurity defense, and is designed for long-horizon tasks requiring deep reasoning and structural precision. Google also provided the Gemini API developer guide and entry points for using it in Google Antigravity and Android Studio. On the same day, Google disclosed an unattended experiment: letting Argon optimize the open-source framework google/adk-python, which has about 205,000 lines of code, within 11 hours. The model proposed 6 optimizations; after human review, 2 were merged into the main branch, memory session preparation time for long sessions was reduced by about 40%, and cold-start import speed improved by 21%. On October 14, Sundar Pichai called this a good summary of the safety and alignment work on Argon 4; Ethan Mollick commented that Gemini 4 is a major leap compared with previous Gemini models but still lags on complex multi-agent tasks. On October 15, Google began rolling out Gemini 4 Argon support to the AI programming tool Antigravity.

Google opens Gemini 4 Argon to developers

On October 13, 2026, Google announced that developers can now use Gemini 4 Argon to build applications. This frontier model targets complex workflows such as real software engineering, enterprise knowledge work, and cybersecurity defense, and is designed for long-horizon tasks requiring deep reasoning and structural precision. Google also provided the Gemini API developer guide and entry points for using it in Google Antigravity and Android Studio. On the same day, Google disclosed an unattended experiment: letting Argon optimize the open-source framework google/adk-python, which has about 205,000 lines of code, within 11 hours. The model proposed 6 optimizations; after human review, 2 were merged into the main branch, memory session preparation time for long sessions was reduced by about 40%, and cold-start import speed improved by 21%. On October 14, Sundar Pichai called this a good summary of the safety and alignment work on Argon 4; Ethan Mollick commented that Gemini 4 is a major leap compared with previous Gemini models but still lags on complex multi-agent tasks. On October 15, Google began rolling out Gemini 4 Argon support to the AI programming tool Antigravity.

View story:Google opens Gemini 4 Argon to developers

Google releases image model Nano Banana 2.1

Google has released Nano Banana 2.1, an image generation and editing model that replaces Nano Banana 2, released in February 2026. According to The Decoder, the company says the new model improves on every front and costs about half as much as its predecessor: 1K images drop from 6.70 cents to 3.36 cents, and 4K from 15.10 cents to 7.56 cents. The model is based on Gemini 3.6 Flash and supports 1K, 2K, and 4K resolutions, can process up to 14 reference images at once while keeping 4 characters and 10 objects consistent, and is being rolled out across the Gemini app, AI Mode in Google Search, Google AI Studio, Flow, Stitch, Google Ads, and the Gemini enterprise platform; the older model gemini-3.1-flash-image will be retired on October 29, 2026. On October 7, Krea announced that Nano Banana 2.1 was live, saying it understands prompts better, edits more sharply, and keeps subjects more consistent, with generation support up to 4K. On October 9, an Artificial Analysis evaluation showed that the model ranks three places higher than Nano Banana 2 on the quality-versus-price frontier, at only half the price.

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Google releases Gemini 3.8 Live audio model

Google released two real-time conversational audio models, Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, available starting today through the Gemini API, Google Workspace, and the Gemini app. According to Google DeepMind, Gemini 3.8 Live Extended Thinking ranks first on the Artificial Analysis Speech-to-Speech Quality Index with a score of 82.6, achieves a 68.6% task completion rate on τ-Voice agent tasks, and scores 97.7% on Big Bench Audio; Gemini 3.8 Live ranks second on the Speech Agent Arena. Both models support near-real-time visual input, automatic switching between 97 languages during a conversation, and can execute tool and API calls in the background without interrupting the conversation. On September 18, Google demonstrated a workshop assistant built with Gemini 3.8 Live Extended Thinking that can analyze the workspace, reason aloud, and guide the building process. On September 21, Google also demonstrated a programming tutoring Agent built with this model that can view the user's screen, reference the p5.js library through function calling, and explain code logic.

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Google DeepMind releases Gemini 3.7 Flash

On August 13, 2026, Google DeepMind released Gemini 3.7 Flash, calling it its strongest flagship model for coding and agents, just three weeks after the release of Gemini 3.6 Flash. Official figures state that the model scored 43.6% on FrontierCode 1.1 Main (34.4% for 3.6 Flash), 65.3% on DeepSWE v1.1 (49.0%), 1588 versus 1538 on WebDev Arena Elo, 34.0% versus 22.0% on GDP.pdf, and 30.4% versus 17.0% on AutomationBench; through the end of the year, introductory pricing is $0.75 per million input tokens and $3.75 per million output tokens, half the original price of 3.6 Flash, and it comes with updated safeguards against CBRN and cyberattack misuse. The next day, Google AI Developers showcased it building a 3D web game with Three.js in Antigravity, as well as generating native code for Flutter, SwiftUI, Jetpack Compose, React Native, and NativeScript from a single architecture spec. On August 17, the company officially demonstrated it extracting historical plants from a Victorian botanical illustrated guide PDF and classifying them according to APG IV; on August 18 it showcased

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Google has released Nano Banana 2.1, an image generation and editing model that replaces Nano Banana 2, released in February 2026. According to The Decoder, the company says the new model improves on every front and costs about half as much as its predecessor: 1K images drop from 6.70 cents to 3.36 cents, and 4K from 15.10 cents to 7.56 cents. The model is based on Gemini 3.6 Flash and supports 1K, 2K, and 4K resolutions, can process up to 14 reference images at once while keeping 4 characters and 10 objects consistent, and is being rolled out across the Gemini app, AI Mode in Google Search, Google AI Studio, Flow, Stitch, Google Ads, and the Gemini enterprise platform; the older model gemini-3.1-flash-image will be retired on October 29, 2026. On October 7, Krea announced that Nano Banana 2.1 was live, saying it understands prompts better, edits more sharply, and keeps subjects more consistent, with generation support up to 4K. On October 9, an Artificial Analysis evaluation showed that the model ranks three places higher than Nano Banana 2 on the quality-versus-price frontier, at only half the price.

View story:Google releases image model Nano Banana 2.1

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Google released two real-time conversational audio models, Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, available starting today through the Gemini API, Google Workspace, and the Gemini app. According to Google DeepMind, Gemini 3.8 Live Extended Thinking ranks first on the Artificial Analysis Speech-to-Speech Quality Index with a score of 82.6, achieves a 68.6% task completion rate on τ-Voice agent tasks, and scores 97.7% on Big Bench Audio; Gemini 3.8 Live ranks second on the Speech Agent Arena. Both models support near-real-time visual input, automatic switching between 97 languages during a conversation, and can execute tool and API calls in the background without interrupting the conversation. On September 18, Google demonstrated a workshop assistant built with Gemini 3.8 Live Extended Thinking that can analyze the workspace, reason aloud, and guide the building process. On September 21, Google also demonstrated a programming tutoring Agent built with this model that can view the user's screen, reference the p5.js library through function calling, and explain code logic.

View story:Google releases Gemini 3.8 Live audio model

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