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Amazon Now Launches 30-Minute Delivery: Swift Logistics For The Modern Consumer

Amazon introduced Amazon Now, a new ultra-fast delivery service offering 30-minute delivery on thousands of products across selected U.S. cities. The launch marks another expansion of Amazon’s rapid delivery network as the company continues investing in faster fulfilment and last-mile logistics capabilities.

New Standard In Speed

Amazon Now allows customers to order products, including groceries, household goods and locally sourced items, with delivery targeted within 30 minutes. The service reflects Amazon’s broader push to reduce delivery times and strengthen convenience-focused shopping options for consumers.

Strategic Geographic Rollout

The service is currently available in markets including Atlanta, Dallas-Fort Worth, Philadelphia and Seattle. Additional expansion is planned across cities, including Austin, Denver, Houston, Minneapolis, Orlando, Oklahoma City and Phoenix. Amazon said the rollout is expected to reach tens of millions of U.S. customers by the end of the year.

A Competitive Pricing Model

Pricing for Amazon Now varies between Prime and non-Prime users. Amazon Prime members pay a delivery fee of $3.99 per order, while non-Prime customers pay $13.99. Smaller orders below $15 may also include an additional fee. The pricing structure places Amazon in more direct competition with delivery platforms including DoorDash, Uber Eats and Instacart.

Optimized Logistics Infrastructure

To achieve these rapid delivery times, Amazon leverages a sophisticated network of smaller fulfilment centres strategically positioned closer to consumers. This targeted approach minimizes travel distances and maintains a curated inventory, ensuring that essential items such as fresh produce, dairy, bakery items, and even electronics are available around the clock in most regions.

Beyond Traditional Delivery

Amazon Now expands the company’s broader same-day and rapid delivery ecosystem, which already includes one-hour, three-hour and same-day shipping options across multiple product categories. The company is also continuing tests of sub-60-minute drone deliveries through its Prime Air programme in selected U.S. locations.

Impressive Growth Metrics

Backed by robust performance figures, Amazon Prime members received over 13 billion items via same-day or next-day deliveries globally in 2025. In the U.S. alone, deliveries surged by 30% year-over-year, a testament to Amazon’s commitment to operational excellence and customer satisfaction.

Senior Vice President of Amazon Worldwide Operations, Udit Madan, encapsulated the initiative by noting, “Amazon Now is for when you need or want the convenience of getting your Amazon order delivered in 30 minutes or less.” This bold entry into ultra-fast delivery further cements Amazon’s reputation as a transformative force in the landscape of retail logistics.

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

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.

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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