# Meta Llama 4 Scout and Maverick Launch with Natively Multimodal Architecture

> Meta has shipped Llama 4 as two open-weight models, Scout and Maverick, and pitched them as the first natively multimodal releases in the family. Instead of bolting vision onto a text model, Meta used an early-fusion design that trains on text, images, and video together from the start. Scout runs on 17 billion active parameters, fits on a single H100, and reportedly beats Gemma 3 and Gemini 2.0 Flash-Lite on benchmarks. Maverick uses a 128-expert mixture-of-experts setup and, per Meta, outperforms GPT-4o and Gemini 2.0 Flash across a broad suite. The eye-catching spec is a 10 million token context window, enough to hold entire codebases or long document sets in one pass. What makes this land is that the weights are open: teams can run, fine-tune, and inspect these models rather than renting them through an API. In a year when the frontier increasingly hides behind closed endpoints, a capable, genuinely multimodal open release keeps pressure on everyone else and hands smaller builders serious capability for free.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: Meta AI · Published Saturday, July 11, 2026_

## Wortins' read

Meta has shipped Llama 4 as two open-weight models, Scout and Maverick, and pitched them as the first natively multimodal releases in the family. Instead of bolting vision onto a text model, Meta used an early-fusion design that trains on text, images, and video together from the start. Scout runs on 17 billion active parameters, fits on a single H100, and reportedly beats Gemma 3 and Gemini 2.0 Flash-Lite on benchmarks. Maverick uses a 128-expert mixture-of-experts setup and, per Meta, outperforms GPT-4o and Gemini 2.0 Flash across a broad suite. The eye-catching spec is a 10 million token context window, enough to hold entire codebases or long document sets in one pass. What makes this land is that the weights are open: teams can run, fine-tune, and inspect these models rather than renting them through an API. In a year when the frontier increasingly hides behind closed endpoints, a capable, genuinely multimodal open release keeps pressure on everyone else and hands smaller builders serious capability for free.

## Source

[Read the full story at Meta AI](https://ai.meta.com/blog/llama-4-multimodal-intelligence/)

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