Meta Developing Image, Video, and Coding AI Models With H1 2026 Target Release

Meta is building out its next generation of AI models across multiple fronts: a new multimedia system capable of generating images and video, plus a dedicated text model optimized for coding. The target? First half of 2026, according to a new report from TechCrunch.

The report offers few specifics on capabilities or architecture, but the timing and scope are telling. Meta isn't just iterating on Llama—it's preparing a multi-modal assault on nearly every frontier where competitors have staked claims.

The Multimedia Play: Taking On Sora and Veo

Video generation has become the new prestige race in AI. OpenAI's Sora captivated the industry when previewed in early 2024, though its public release came with significant content restrictions. Google's Veo has shown impressive results in controlled demos. Runway and Pika have carved out the prosumer market.

Meta's entry into image and video generation isn't surprising—it's overdue. The company has dabbled with tools like Emu for image generation, but nothing that competes at the frontier. With Instagram and WhatsApp commanding billions of users who create and consume visual content daily, Meta has both the distribution and the incentive to own this stack.

An H1 2026 timeline gives Meta roughly 18 months of development runway. That's aggressive for a from-scratch video model, suggesting either significant work already underway or a scope more limited than what Sora promises.

The Coding Model: A Llama Extension or Something New?

More intriguing is the reported coding-focused text model. The AI coding assistant market has exploded, with GitHub Copilot now embedded in millions of developer workflows, Cursor rethinking the IDE entirely, and Anthropic's Claude gaining reputation as the preferred model for complex programming tasks.

Meta's Llama models have performed respectably on coding benchmarks, but they haven't been purpose-built for the task. A dedicated coding model could change that—and given Meta's open-weight philosophy with Llama, a strong open-source coding model would be a genuine contribution to the ecosystem.

The question is whether Meta releases this as an open-weight model or keeps it proprietary. Open release would undercut Copilot's business model and give every startup a foundation to build on. Proprietary release would suggest Meta sees direct revenue potential, perhaps through developer tools or enterprise services.

The Broader Strategy

Mark Zuckerberg has been clear about Meta's AI ambitions: build leading models, release them openly when possible, and integrate them deeply into Meta's consumer products. The company has reportedly spent heavily on Nvidia GPUs and is building out custom silicon.

This multi-model approach—multimedia generation plus specialized coding—suggests Meta is moving past the "one model to rule them all" thinking. Different tasks may need different architectures, different training approaches, different inference optimizations.

For the industry, Meta's continued investment means the AI race stays hot through 2026 and beyond. For developers and creators, it likely means more powerful, more accessible tools—especially if Meta stays true to its open-weight commitments.

The details remain thin. But the direction is clear: Meta wants to compete everywhere AI matters.