Google Expands Gemini’s Personalized Image Generation To More U.S. Users

Google is expanding access to one of Gemini’s AI features, making personalized image generation powered by Nano Banana available free of charge to all eligible users in the United States. Previously, the capability was limited to Gemini Plus, Pro and Ultra subscribers.

Personalization Reaches A Wider Audience

The feature launched in April as part of Gemini’s Personal Intelligence offering, which is designed to generate images based on a user’s interests and preferences. Instead of relying solely on detailed prompts, Gemini can draw on information from a user’s Google ecosystem to tailor image requests.

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For example, users can ask Gemini to “create an illustration of me and my favorite things,” with the system using information from connected services such as Gmail, Google Photos, YouTube and Search to personalise the result.

Google Photos Expands Image Generation

The feature can also access images stored in Google Photos, allowing users to generate personalised content without uploading reference photos manually.

Google first introduced Personal Intelligence to U.S. users in March before expanding the feature to India and Japan. The rollout of Nano Banana-powered image generation extends those capabilities to a broader group of users.

Users Remain In Control

According to Google, Personal Intelligence is an opt-in feature, allowing users to decide which Google apps Gemini can access. Once enabled, it becomes the default setting for relevant prompts, although it can be turned off at any time through the Tools menu.

Gemini Expansion Continues

The latest update comes as Google continues to expand Gemini’s capabilities. Last month, the company announced several upcoming additions, including a Daily Brief feature, a redesigned interface, access to the Gemini Omni video model, and a personal AI agent called Gemini Spark.

Earlier this year, Google also said Gemini had surpassed 750 million monthly active users, highlighting the platform’s growing adoption.

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Meta Unveils Muse Wonder Models In A Bid For Frontier AI Leadership

by THEFUTURE.TEAM

October 13, 2026

Meta has introduced two new AI models, Muse Wonder and Muse Wonder Full, signalling a more ambitious move into frontier AI. The releases build on Muse Spark but target more demanding tasks, including coding, while placing greater emphasis on long-term memory and personalised assistance.

Larger Models Target More Demanding Tasks

Unlike Muse Spark, which was designed for low latency and lightweight use, Muse Wonder and Wonder Full are significantly larger and, according to Meta, more capable. The company reports stronger benchmark performance and improvements on demanding workloads, including coding.

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According to Meta’s model card, both models achieved benchmark results comparable to Fable 5.1 and GPT-6 Astra in the company’s internal testing. Meta described the release as “the next step on our scaling ladder and a major leap toward personal superintelligence” in its announcement.

Pricing Reflects Meta’s Frontier Ambitions

The models’ pricing places them in the premium AI segment. Through the Meta Model API, Muse Wonder will cost $4 per million input tokens and $20 per million output tokens, putting it in a similar pricing tier to GPT-6 Sol and Opus 5.5.

Muse Wonder Full, by contrast, will not be offered through the API. Meta says it will be exclusive to Muse Code subscribers, tying access to its most advanced model to a premium product. Both models will also power the Muse agent.

Long-Term Memory Takes Centre Stage

Meta is increasingly positioning its AI strategy around assistants that can support users over time rather than respond only to individual prompts. A central part of that approach is what the company calls “active memory”: the ability to retain, organise and synthesise information provided by users across extended periods.

Meta points to the MemoryBench benchmark, which evaluates systems designed for continual learning and memory construction. The company says Muse Wonder now outperforms Fable, Opus and Astra on this measure.

“We put a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond,” research scientist Kavya Kopparapu said in a launch video.

New Models Follow Meta’s AI Reorganisation

The launch is also significant within Meta’s broader AI strategy. It is the company’s first frontier-model release since Scale AI founder Alexandr Wang reorganised its AI operations in August 2025. Meta has since introduced Muse Spark and the Muse agent, while making fewer high-profile model announcements than competitors such as OpenAI and Anthropic.

The new models were trained at Meta’s Prometheus data centre in central Ohio, which came online earlier in 2026, according to the company. The facility highlights the growing importance of infrastructure in the race to develop advanced AI systems, where performance depends not only on algorithms and data but also on computing capacity, data-centre investment and access to capital.

As competition intensifies, Muse Wonder and Wonder Full represent a broader bet on larger models, persistent memory and premium AI products. Their longer-term significance will depend on how their reported capabilities translate into real-world performance and whether users find enough value to pay for access.

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