Meta has outlined the full breadth of its AI strategy, spanning custom silicon, open-source large language models, consumer products, and a stated philosophical commitment to decentralised AI — positioning itself against rivals it claims want to direct superintelligence from the top down.
The snapshot, drawn from Meta's AI homepage, arrives at a moment when the company is accelerating across every layer of the AI stack simultaneously. From designing its own inference chips to shipping AI-powered glasses in partnership with Oakley, Meta is pursuing a strategy that is simultaneously vertical — controlling hardware, models, and applications — and open, with its Llama model family available for public download.
Four Chips in Two Years: Meta's Silicon Ambition
Perhaps the most technically significant disclosure is Meta's chip cadence. The company states it has shipped four generations of its Meta Training and Inference Accelerator (MTIA) chips in just two years — a pace that signals serious intent to reduce dependence on third-party GPU suppliers. A blog post dated March 11, 2026 details how MTIA is being scaled to serve AI experiences for billions of users across Meta's platforms.
Alongside its internal silicon effort, Meta announced a long-term AI infrastructure agreement with AMD, disclosed on February 24, 2026. The partnership adds a strategic hardware supply relationship to complement MTIA development, suggesting Meta is hedging across both proprietary and partner silicon — a prudent posture given ongoing GPU supply constraints industry-wide.
Meta's vision is to bring personal superintelligence to everyone — distinct from others who believe superintelligence should be directed centrally towards automating all valuable work.
Llama 4 and the Open-Model Wager
On the model side, Meta is promoting Llama 4 as its flagship open large language model, featuring a mixture-of-experts architecture, native multimodal capabilities, and what the company describes as near-limitless context windows. The model is available for download, continuing Meta's open-release strategy that has made the Llama family one of the most widely deployed model lines outside of closed commercial APIs.
Case studies on the Llama site show real-world deployments: Shopify using Llama to optimise product listings from images, a healthcare company called Benete applying it to elderly care workflows, and Upwork using it to help freelancers win business. These examples are strategically chosen — they demonstrate Llama's commercial utility without Meta needing to operate the end product, reinforcing the open-ecosystem argument.
Consumer Products: Vibes, SAM 3, and AI Glasses
On the consumer and product side, Meta's most prominent new feature is Vibes — an AI video creation tool launched in September 2025 that lets users generate immersive, personalised video content. Vibes is integrated into the Meta AI app, where users can add themselves and friends to AI-generated scenes. It represents Meta's entry into the generative video space occupied by competitors such as OpenAI's Sora and Google's Veo.
Segment Anything Model 3 (SAM 3), released November 19, 2025, extends Meta's computer vision research into a publicly accessible playground. Using text and visual prompts, SAM 3 can detect, segment, and track any object across images and video — with applications ranging from content moderation to augmented reality.
Hardware is also central to Meta's consumer push. The Oakley Meta Vanguard AI glasses, announced in September 2025, target the performance sports market — a higher-specification sibling to the existing Ray-Ban Meta smart glasses line. Embedding AI into wearables gives Meta a sensor-rich access point to ambient computing that no software-only competitor can replicate.
Research Pillars: From World Models to Alignment
Meta's research organisation is structured around six areas: Communication & Language, Embodiment & Actions, Alignment, Core Learning & Reasoning, Coding, and Perception. Notable outputs include V-JEPA 2, described as a world model trained on video to achieve state-of-the-art visual understanding, and DINOv3, a self-supervised vision model trained at unprecedented scale.
The Alignment pillar explicitly covers AI for science and AI for society — a nod to the governance scrutiny that Meta, like all frontier AI developers, faces from regulators in the US and EU. How that research translates into product safeguards remains, per Meta's own framing, an ongoing area of work rather than a solved problem.
The 'Personal Superintelligence' Framing
Meta's philosophical positioning deserves attention. The company explicitly contrasts its vision — AI power distributed to individuals — against unnamed competitors who, it claims, believe superintelligence should be directed centrally and that humanity will subsist on its automated output. The target of that critique is not difficult to infer, given public statements from OpenAI and others about AI-driven economic transformation.
Meta's framing serves a dual purpose: it differentiates its brand in a crowded market, and it provides a values argument for open-source release. If AI capability is decentralised through open models, no single actor — including Meta — controls the output. Whether that argument holds as models become more powerful is a debate the industry has not resolved.
What This Means
Meta is building a closed-loop AI ecosystem — custom chips, open models, consumer hardware, and a philosophical narrative — that makes it structurally distinct from both closed-API competitors like OpenAI and pure cloud providers like Google and Microsoft. Companies and developers evaluating AI partnerships should treat Meta as a full-stack contender, not merely a social media company with a model lab.