Meta Delays New AI Model: Even Big Tech Struggles in the AI Race

The New York Times is reporting that Meta has delayed launching its next-generation Avocado AI model. The model is reportedly underperforming compared to competitors like OpenAI and Google, raising questions about whether Meta can keep up in the AI race.

What’s Being Reported

According to industry sources, Meta’s development of its next major AI model — codenamed “Avocado” has been pushed back. The company isn’t hitting quality targets internally. The reasons:

• The model isn’t matching the performance of competitors like Google Gemini and OpenAI’s GPT-5.4
• Meta is still investing tens of billions of dollars into AI development
• There’s even internal discussion about potentially integrating rival models instead of going it alone

This isn’t the first time Meta has fallen behind in the current AI wave. While the company was an early leader in deep learning research, but they’ve struggled to convert that research into a product that competes with the top models from OpenAI and Google.

The Cost Problem

The core issue here isn’t lack of effort or talent — it’s scale. Training frontier AI models now costs billions of dollars in compute resources. Meta has certainly spent the money — over $100B is already invested according to reports — but they still haven’t caught up.

This raises an interesting question: can multiple companies can afford to play at the frontier of AI model development? Right now, only a handful of tech giants have the balance sheet to play this game. Even for them, it’s not clear that all of them will succeed.

Why This Matters

The fact that even a company as large and capable as Meta is struggling tells us something important about the current AI race:

1. The bar is getting higher every six months: What was state-of-the-art today isn’t good enough a year later
2. Compute isn’t everything: Money and talent don’t automatically translate to commercial success
3. Consolidation might happen: We could see fewer independent players in the frontier model game
4. Partnerships might become the norm: We could see more companies relying on each other’s models instead of building everything from scratch

Industry Implications

If even Meta is struggling, what does that mean for smaller players? It suggests that the era of “everyone builds their own giant foundation model” is already coming to an end. Going forward, we’ll probably see:

• A small number of frontier foundation model providers
• More companies building applications on top of those models instead of training their own
• More partnerships and collaborations between companies that don’t want to spend billions on training

This isn’t the end of Meta in AI — they’re still a major player in infrastructure and applications — but it does show that the frontier model game is getting harder than many expected.

Source: Latest AI News (March 2026) – The AI Woods | Published: March 24, 2026