Meta reportedly developing next-generation AI model Avocado, set for 2026 launch

Meta is developing a next‑generation AI model codenamed Avocado as a potential successor to its open‑source Llama series, targeting a first‑quarter 2026 launch and signaling a shift toward a more proprietary approach. The rollout, initially expected in 2025, has been pushed while Meta addresses performance‑testing and training challenges, though the company says training timelines are unchanged; the effort accompanies leadership changes and a major talent push, including a reported $14.3 billion hiring outlay in June to recruit Scale AI founder Alexandr Wang and other engineers to better compete with OpenAI, Google and Anthropic. Meta shares were down 1.5% at $657 on Tuesday but remain up about 12% year‑to‑date.

Analysis

Meta is developing a next-generation AI model codenamed Avocado as a potential successor to its open-source Llama series, targeting a first-quarter 2026 launch and signaling a move toward a more proprietary approach. The rollout was initially expected before the end of 2025 but is reported to be delayed by performance testing and training challenges; Meta spokespersons counter that model training efforts remain on schedule.

The program sits alongside leadership changes and a substantial talent investment: the article cites a June hiring outlay of $14.3 billion to recruit Scale AI founder Alexandr Wang and other senior engineers and researchers to compete with OpenAI, Google and Anthropic. That spend elevates execution priority and raises expectations for differentiation versus rivals, but also concentrates risk on successful training and benchmarking.

Market reaction to the news was muted-to-cautious: Meta shares traded down 1.5% at $657 on the report while remaining up about 12% year-to-date, and the sentiment signal in the dataset is mildly positive with a modest market-impact score. Key near-term risks are further slippage in the timeline and unresolved performance issues; key catalysts to watch are technical benchmark releases, training-completion updates, and explicit commercialization/licensing plans.

Key Decisions for Investors

• Monitor Meta disclosures for concrete training milestones and performance benchmarks ahead of Q1 2026 and treat those updates as primary catalysts for repositioning
• Avoid increasing unhedged exposure on headline momentum alone given reported delays and technical risk; consider trimming leveraged positions if the company misses interim milestones
• View the $14.3 billion talent push as a constructive long-term strategic signal and consider modest incremental exposure on material weakness, but only after clearer go-to-market and licensing details emerge
• Watch competitive responses from OpenAI, Google and Anthropic and reassess valuation sensitivity to a shift from open-source Llama to a proprietary Avocado model as developer adoption and monetization clarity evolve