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Tesla’s Growth Trajectory Falters Amid Modest Q1 Deliveries

Tesla’s Delivery Numbers Under Pressure

Tesla launched lower-priced versions of Model Y and Model 3 at $39,990 and $36,990 after ранее announced plans to expand its affordable EV lineup. Early data indicate the new pricing has not materially increased overall deliveries.

Production Over Sales: The Q1 Figures

Tesla delivered 358,023 vehicles globally in the first quarter, below analyst expectations of around 368,000 units. Production reached 408,386 vehicles, exceeding deliveries and adding to inventory. Year-on-year, deliveries increased by 6% compared to Q1 of the previous year, which had been affected by production line adjustments. The latest figures suggest limited improvement in demand despite higher output.

An Industry Facing Growing Headwinds

Performance at Tesla reflects broader trends across the U.S. electric vehicle market. Several traditional automakers have reduced EV expansion plans, while newer entrants continue to scale gradually. Rivian reported steady shipment levels and is preparing to launch the R2 SUV, with entry-level models expected by 2027.

Strategic Shifts And Future Prospects

Tesla shifted focus away from a previously discussed $25,000 EV toward projects such as CyberCab and existing models. Elon Musk has prioritised autonomous and platform development over lower-cost mass-market vehicles. Cybertruck remains the only recent new model, while sales across other models show slower momentum compared to earlier growth periods.

Looking Ahead

Tesla now faces the dual challenge of revitalizing its growth trajectory and addressing the competitive pressures that have gripped the entire electric vehicle market. With both sales and profits under scrutiny, the coming quarters will be critical for Tesla in demonstrating that its ambitious promises can translate into sustainable results.

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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