Published December 19, 2025 · Updated December 19, 2025
Why this matters
The competitive front line in artificial intelligence is shifting again — this time toward richer generative media and fully multimodal systems. With the quiet development of new AI models code-named Mango (image and video) and Avocado (text), Meta is signaling a strategic recalibration: generative AI is no longer just about language, but about end-to-end creative systems embedded directly into platforms people already use.
This matters because Meta’s scale — spanning social media, creator ecosystems, and advertising — gives it a unique ability to operationalize multimodal AI at consumer scale. While OpenAI and Google compete on frontier models and APIs, Meta appears to be optimizing for native integration, creator tooling, and immersive content formats.
This development reinforces the broader shift we’ve outlined in Generative AI Explained, where image, video, and text generation are converging into unified creative systems.
Key Takeaways
- Meta is developing Mango, a next-generation AI model for image and video generation
- Avocado expands Meta’s text-based generative capabilities
- The strategy points to deeper multimodal AI experiences across Meta platforms
- Generative media is becoming central to creator tools and social engagement
- Meta is strengthening its AI talent bench to compete with OpenAI and Google
Meta’s “Mango” and the Push Toward Generative Media
According to reporting by The Wall Street Journal, Meta is internally developing Mango, an AI model designed for high-quality image and video generation. While Meta has previously released open models and research-oriented tools, Mango appears aimed at production-grade generative media rather than experimentation.
This suggests a shift in emphasis. Instead of focusing solely on benchmark performance, Meta is prioritizing media realism, controllability, and platform readiness — key requirements for large-scale deployment across Instagram, Facebook, and future immersive environments.
The move aligns with a broader industry realization: as generative AI matures, value increasingly comes from how seamlessly models integrate into existing ecosystems, not just how impressive they look in isolation.
Avocado and the Evolution of Text-Based AI at Meta
Alongside Mango, Meta is also advancing Avocado, a next-generation text model intended to complement its generative media stack. While details remain limited, Avocado appears positioned as a foundational language layer supporting multimodal reasoning, content understanding, and creator assistance.
This reflects an important architectural shift. Modern AI systems are no longer siloed by modality. Text, images, video, and structured signals are increasingly co-dependent, requiring coordinated model design rather than standalone releases.
This mirrors themes explored in How Artificial Intelligence Works, where model capability alone rarely determines real-world impact — system integration and orchestration matter just as much.
Multimodal AI as a Platform Strategy
Multimodal AI is often framed as a technical milestone, but for Meta it is fundamentally a platform strategy. Social and creator platforms thrive on rich media: short-form video, visual storytelling, and interactive formats. Generative AI that can fluidly operate across these modalities enables:
- Faster content creation for creators
- New advertising and personalization formats
- AI-assisted editing, remixing, and augmentation
- Deeper engagement without increasing production friction
Rather than selling APIs to enterprises, Meta is embedding AI directly into consumer and creator workflows, turning generative models into invisible infrastructure rather than headline products.
Strategic Context: Talent, Scale, and Quiet Execution
Meta has also been quietly reinforcing its AI talent bench, recruiting researchers and engineers with experience in large-scale multimodal systems. Unlike more public AI races, Meta’s approach appears deliberately low-noise — shipping capabilities incrementally rather than announcing grand unified models.
This strategy reflects Meta’s long-standing advantage: distribution at scale. If Mango and Avocado mature into production systems, Meta can deploy them instantly to billions of users — a capability few competitors possess.
In that sense, Meta’s AI strategy is less about winning benchmarks and more about shaping everyday digital experiences.
Practical Implications for Creators and Businesses
For creators
- AI-assisted image and video generation lowers production barriers
- Faster experimentation with formats and visual styles
- Increased competition as generative content becomes ubiquitous
For businesses and marketers
- New AI-driven creative tooling inside Meta’s ad ecosystem
- Greater automation in campaign creation and optimization
- Rising importance of differentiation as content supply explodes
For the AI ecosystem
- Multimodal systems are becoming the default, not the exception
- Platform-native AI may outcompete standalone tools in consumer contexts
- The race increasingly favors companies with both models and distribution
Competition in the Generative AI Landscape
Mango and Avocado enter a crowded field where OpenAI, Google, and others are pushing rapidly forward. The key difference is positioning. While some players optimize for developer platforms and enterprise APIs, Meta is betting on deep vertical integration with social and creative platforms.
The competitive question is no longer who builds the most capable model, but who controls the surfaces where AI is actually used.
What Happens Next
Meta’s Mango and Avocado projects suggest that the next phase of generative AI will be defined less by headline launches and more by quiet, systemic integration. If successful, these models could fundamentally reshape how content is created, distributed, and monetized across social platforms.
At Arti-Trends, we track these developments closely because they reveal how AI leaders expect generative systems to function — not in demos, but in the daily workflows of creators, businesses, and users worldwide.
Sources
- The Wall Street Journal — reporting on Meta’s internal AI development
- Meta AI research and public disclosures
