Meta is widening its AI effort on two fronts at once: a dedicated assistant app for everyday users and a Llama API platform for developers. The announcements, made at its first LlamaCon developer conference, show how the company is trying to make Meta AI more visible to consumers while making Llama models easier to build with.
A standalone app changes the role of Meta AI
The Meta AI app is Meta's first dedicated app for its AI assistant. Instead of living only inside other Meta products, the assistant now has a separate place where users can start conversations, ask for help and work with AI-generated content.
According to Meta, the app is designed to feel more personal over time. It can adapt to user preferences and keep context across conversations, which matters because an assistant becomes more useful when it can remember what a person is trying to do rather than treating each request as isolated.
The app supports text and voice interaction, image generation and image editing. It can also provide recommendations. The product runs on Meta's latest Llama 4 model, while voice features are still in testing and are available in the US, Canada, Australia, and New Zealand.
That gives Meta a clearer answer to ChatGPT in the consumer AI market. The source notes that current features may not fully match OpenAI's offering, but it is not yet clear how much ordinary users will notice those differences in daily use.
Meta's ecosystem gives the assistant a built-in path
The app is not being introduced in isolation. Meta can connect the assistant to a large existing social media network, which gives it a distribution advantage. The comparison in the source is Google's integration of Gemini into Search: when an AI tool is placed near services people already use, discovery becomes easier.
Meta is also tying the assistant to its broader ecosystem. A conversation can begin in the app and continue on desktop or on Ray-Ban Meta smart glasses. The app also acts as a central hub for managing AI-enabled devices.
That hub role is important because it positions the Meta AI app as more than a chatbot window. It becomes a control point for AI interactions across devices, which could make the assistant feel less like a single product and more like a layer across Meta's hardware and software.
Social discovery becomes part of the AI experience
Meta is adding a social layer through a feature called the Discover Feed. The feed lets users see how other people interact with the AI, share prompts and post their own content when allowed.
This approach treats AI use as something people may want to observe, borrow from and share, not only as a private exchange between one user and one assistant. Prompt sharing can also make the app easier for new users, because examples show what the assistant can do without requiring people to know the right way to ask.
The source also says OpenAI is reportedly developing similar social networking features, with the company's Sora image and video feed described as a likely candidate for that kind of expansion. That suggests social AI feeds may become a more common part of consumer AI products, especially where images, videos and prompts are central to the experience.
The Llama API lowers the barrier for developers
Alongside the app, Meta introduced the Llama API. The platform lets developers generate keys quickly and use interactive testing environments for different Llama models, including Llama 4 Scout and Llama 4 Maverick.
Before this, developers had to use the models through self-hosting or select cloud providers. The new API gives Meta a more direct route to developers who want to test, prototype and deploy with Llama without first managing the infrastructure themselves.
SDKs are available for Python and TypeScript. Meta also intends compatibility with the OpenAI SDK to make it easier to move existing applications. That detail matters because many developers already have tools and workflows built around existing AI interfaces, and migration friction can slow adoption.
The platform also supports fine-tuning for Llama 3.3 8B using Meta's toolkit for data generation, training and quality evaluation. Trained models can be exported and hosted outside Meta. Meta says user content will remain private and will not be used to train their models.
Meta has also partnered with Cerebras and Groq so developers can test Llama models on specialized hardware through centralized billing. The company expects more hardware providers to join the platform in the future. Developers seeking early access can join the waiting list, and a demonstration of the app and API is available in Meta's presentation video starting at the 30-minute mark.
Safety tools round out the platform story
Meta also announced new safety tools as part of the Llama push. The list includes Llama Guard 4, LlamaFirewall and Llama Prompt Guard 2.
These tools are meant to help reduce risks from malicious prompts or attacks. For developers and organizations, that matters because model access is only one part of deploying AI; systems also need protections around how prompts, outputs and application flows are handled.
The Llama Defenders Program adds a partner network for organizations assessing the security of their AI systems. Together, the assistant app, Llama API, hardware partnerships and safety tools show Meta trying to cover both sides of the market: people who want a ready-to-use assistant and developers who want models they can build into their own products.