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- 🚨 Meta Delays Release of New AI Model “Avocado”
🚨 Meta Delays Release of New AI Model “Avocado”
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Meta has reportedly delayed the launch of its next major AI model, internally code-named “Avocado.”
The model was originally expected to launch this month but is now pushed back until at least May, according to people familiar with the project.
⚠️ Why the Delay Happened
The delay comes after internal testing showed the model wasn’t performing as well as rival AI systems.
Reports suggest Avocado struggled to match the latest models from competitors such as:
• OpenAI
• Google
• Anthropic
Meta is now refining the system before public release.
🧠 Meta’s Massive AI Ambitions
Despite the delay, Meta is aggressively investing in AI.
The company announced $115–$135 billion in capital spending for 2026, aimed at building systems capable of reaching superintelligence — AI that could surpass human capabilities.
Major focus areas include:
• training next-generation AI models
• building custom AI chips
• expanding global data centers.
🤯 A Surprising Backup Plan
According to reports, Meta executives have also discussed a temporary solution:
Licensing AI technology from Google.
Specifically, Meta considered using the model from Gemini to power some of its AI products while its own models improve.
No final decision has been made.
📈 Meta’s Strategy
Meta’s approach is not about one single model release.
Instead, the company plans rapid iterative improvements throughout the year.
A spokesperson said the next model will demonstrate:
• strong performance gains
• a clear trajectory of improvement
• continued frontier progress.
🌍 Why This Matters
The delay highlights how intense the AI race has become.
Tech giants are competing to build the most powerful AI models while spending hundreds of billions on infrastructure.
Even a small performance gap can delay launches.
📌 Bottom Line
Meta isn’t slowing down — it’s recalibrating.
“Avocado” may arrive later than planned, but the company is betting that massive infrastructure investment and rapid iteration will eventually close the gap in the AI race.
