Artificial intelligence has entered a new phase—one where visual intelligence is becoming just as important as text-based reasoning. Over the past few years, image and video generation models have evolved from experimental tools into core technologies powering advertising, entertainment, social media, and design workflows. In this rapidly evolving landscape, Meta is developing a new image and video model for a 2026 release, signaling a major strategic push by the company to redefine how visual AI is built and deployed at scale.
This initiative goes beyond feature upgrades or short-term experimentation. Meta’s upcoming model is expected to serve as a foundational system capable of understanding, generating, and editing both images and videos across its ecosystem—including Facebook, Instagram, WhatsApp, and future mixed reality platforms. As competitors like OpenAI and Google accelerate their multimodal AI roadmaps, Meta’s move reflects both competitive urgency and long-term ambition.
In this article, we’ll explore what Meta’s new image and video model is, why the company is building it, when it’s expected to launch, how it compares to rival offerings, and what it could mean for creators, advertisers, and the broader AI industry.
What Is Meta’s New Image and Video Model?
Meta’s upcoming system—internally referred to by the codename Mango—is being designed as a next-generation image and video foundation model. Unlike earlier AI tools that focused on static images or short-form clips, this model aims to handle both visual formats within a unified architecture.
The goal is to build a system that can interpret visual context across frames, understand motion and scene continuity, and generate high-quality outputs that feel coherent and realistic. This approach places Meta’s efforts squarely within the broader shift toward multimodal AI, where models can seamlessly process text, images, video, and audio together.
What the Model Is Designed to Do
- Generate high-quality images and videos from text prompts
- Understand motion, objects, and context across video frames
- Edit and transform existing visual content
- Support real-time or near-real-time visual AI applications
In practical terms, Meta is building a visual AI system that can both see and create—a critical capability for platforms centered around user-generated content.
Why Meta Is Building This Model
Meta has already made substantial investments in large language models through its LLaMA family. However, text-based intelligence alone is insufficient for a company whose products revolve around photos, videos, stories, and short-form content. Instagram Reels, Facebook video, and future augmented reality experiences demand advanced visual understanding.
The new image and video model fits into Meta’s broader AI roadmap by complementing its language models and enabling fully integrated multimodal systems. Together, these technologies allow Meta to deliver richer, more interactive, and more personalized experiences across its platforms.
Expected Release Timeline: First Half of 2026
According to industry reporting and internal signals, Meta’s image and video model is expected to launch in the first half of 2026. While this timeline may seem distant, it reflects the complexity involved in training large-scale video models and deploying them responsibly.
Video AI requires significantly more compute and data than image generation. Each second of video contains dozens of frames, along with temporal relationships, motion physics, and audio-visual alignment. Meta’s longer development cycle suggests a focus on robustness, scalability, and deep platform integration rather than rushing to market.
The 2026 timeline also aligns with broader infrastructure upgrades, next-generation AI hardware, and Meta’s long-term plans around immersive computing and spatial experiences.
How Meta Compares to Competitors
Meta is entering an increasingly competitive field. Several major technology companies are racing to build the most capable visual AI systems.
Google has developed advanced image and video capabilities through models such as Imagen and its Gemini multimodal framework. Its strength lies in enterprise applications and search integration, though consumer-facing creative tools have been rolled out more cautiously.
OpenAI
OpenAI has set high benchmarks for image generation and multimodal reasoning. However, it lacks a native social platform where visual AI can be deployed at the scale Meta operates.
Meta’s Strategic Advantage
Meta’s biggest differentiator is distribution. With billions of users actively creating and consuming visual content, Meta can rapidly test, refine, and deploy visual AI features in real-world environments. This makes its image and video model not just a technical asset, but a platform-level advantage.
Potential Use Cases Across Meta Platforms
Once deployed, Meta’s new image and video model could enable a wide range of applications.
For Social Platforms
- AI-powered content creation for Reels and Stories
- Automated video editing and background generation
- Improved accessibility through visual descriptions and captions
For Creators and Advertisers
- Faster production of marketing visuals
- Dynamic, personalized ad creatives
- Localized video content at scale
For Future AR and Metaverse Experiences
- Real-time environment generation
- More realistic avatar animation
- Spatial video understanding for mixed reality
Challenges and Risks Meta Faces
Despite its resources, Meta faces several hurdles in bringing this model to market.
Technical Challenges
- Training stable, high-quality video models at scale
- Reducing visual hallucinations and inconsistencies
- Managing compute costs and energy consumption
Ethical and Legal Concerns
- Copyright and data licensing issues
- Potential misuse for deepfakes and misinformation
- Bias and representation in generated visuals
Successfully navigating these challenges will be critical to ensuring trust and long-term adoption.
Conclusion: Why This Matters
Meta’s decision to build a unified image and video model underscores a broader industry shift toward multimodal AI systems. If successful, this technology could reshape how content is created, shared, and monetized across Meta’s platforms and beyond.
As 2026 approaches, Meta’s progress will be closely watched—not just by competitors, but by creators, advertisers, and policymakers alike. The outcome could define the next chapter of visual AI at global scale.
Frequently Asked Questions
What is Meta’s new image and video model?
It is a next-generation AI system designed to generate, understand, and edit images and videos across Meta’s platforms.
When will Meta release this model?
Current reports indicate a release in the first half of 2026.
What does the codename Mango refer to?
Mango is the internal name reportedly used for Meta’s image and video foundation model.
How does this compare to OpenAI and Google?
Meta’s key advantage lies in massive consumer distribution, while competitors lead in enterprise and developer ecosystems.
Who will benefit most from this model?
Creators, advertisers, businesses, and users across Meta’s platforms are expected to benefit from faster, smarter visual content creation.