This is one of those stories that sounds embarrassing for Meta but could end up being good news for small businesses.
According to reporting from The New York Times and earlier details from The Information, Meta has delayed its new internal model, code-named Avocado, from March until at least May after it underperformed on internal benchmarks. The model reportedly beat Llama 4 but still landed somewhere between Gemini 2.5 and Gemini 3, not where Meta wanted it relative to Google, OpenAI, Anthropic, and xAI.
The more interesting twist is the backup plan. Meta is now reportedly considering licensing Google's Gemini to power Meta AI products in the interim, potentially under a deal structure similar to the one Apple reportedly struck for Gemini access.
If that happens, small businesses should not treat it as a failure that makes Meta less useful. They should treat it as a possible upgrade.
What happened with Avocado
Meta has spent aggressively to stay in the frontier model race. Reports peg the company's new AI talent push at roughly $20 billion and this year's data center spend at around $135 billion. That is real money, even by big tech standards.
And yet the result appears to be the same lesson the rest of the market keeps learning: building frontier AI is brutally hard.
Avocado was reportedly supposed to arrive in March. Instead, it slipped to at least May after internal testing showed it was not competitive enough. Ethan Mollick at Wharton summed up the broader picture well: "Frontier AI models are really a three-way race at this point."
That is a blunt way of saying the top tier still looks like Google, OpenAI, and Anthropic, while everyone else is trying to close the gap.
Why the Gemini rumor matters more than the delay
Most business owners do not care whether Meta built the model itself. They care whether the tools they use every day actually work.
That is why the Gemini licensing piece matters.
If Meta starts using Gemini inside parts of its AI stack, the practical result for SMBs could be:
- better answers inside WhatsApp Business conversations
- stronger drafting and support help in Instagram DMs
- better creative assistance and targeting support inside Facebook and Instagram ads
- more reliable internal assistants across Meta's business tools
In plain English, if Meta swaps in a better brain, your team gets better output. That is the part worth watching.
This is the real lesson for SMBs
A lot of small business owners still assume the long-term goal is to build "their own AI." In most cases, that is the wrong goal.
Meta is one of the richest companies on earth. It has world-class researchers, enormous compute budgets, and direct control over massive consumer products. Even Meta is struggling to produce a frontier model that clearly beats what is already on the market.
So no, your local services business, ecommerce brand, agency, or multi-location company probably does not need to build a foundation model.
You need to do something much simpler and much more valuable:
- Pick the best models already available.
- Put them into the workflows that matter.
- Switch when a better option shows up.
That is the winning play.
What small businesses should do right now
If your company relies on Meta's ecosystem for customer communication or marketing, this story is worth paying attention to for a very practical reason: the quality of the underlying model affects the quality of your day-to-day work.
Here is the smart response.
1. Stay flexible about vendors
Do not get emotionally attached to any one AI brand. If Meta uses its own model, fine. If it licenses Gemini, also fine. Judge the output, not the org chart.
2. Watch the channels where Meta AI actually touches your business
For most SMBs, that means:
- WhatsApp Business
- Instagram inbox workflows
- Facebook and Instagram ad tools
- customer support and lead qualification flows tied to Meta properties
Those are the places where a model upgrade would become visible fast.
3. Optimize around results, not ownership
The best AI stack for a small business is rarely "all from one company." It is usually a mix of tools that each do their job well. If Gemini improves Meta's products, that is not messy. That is useful.
The bigger market signal
This story also says something important about the state of AI competition in 2026.
The market keeps getting framed as an arms race where every giant tech company will eventually have an equally strong model. That has not happened. Training budgets are exploding. Expectations are rising. But model quality is still uneven, and the gap between first tier and second tier is real.
That matters because it should change how buyers think.
The question is not, "Which company can tell the best AI story?"
The question is, "Which product gives my team the best output today?"
If Meta answers that question by licensing Gemini while it fixes Avocado, that is a perfectly rational move. It may also be the fastest path to making Meta AI more useful for the businesses already living inside its ecosystem.
Bottom line
Meta delaying Avocado is a reminder that frontier AI is still hard, even for trillion-dollar companies spending at absurd scale.
But the possible Gemini licensing deal is the part small businesses should care about most. If Meta plugs a top-tier model into WhatsApp, Instagram, and Facebook workflows, SMBs could get a meaningful quality jump without changing platforms.
That is the lesson here: stop worrying about who built the model and start focusing on whether the tool helps your business run better.
If you want help choosing the right AI stack for marketing, support, and internal workflows, contact Barista Labs.