Meta announced Llama 4 Scout and Maverick on April 5, 2025, and previewed Behemoth, which was still training and not yet released at that time. Scout is the smaller option by total model size, with a context window Meta described as 10 million tokens; Maverick has more experts and was positioned for general assistant and chat use. These are open-weight models, distinct from Meta AI, the consumer-facing service.
What Meta announced as Llama 4
Meta’s April 5, 2025 announcement introduced Scout and Maverick as its first Llama 4 models, describing them as open-weight, natively multimodal models built with a mixture-of-experts (MoE) architecture. Meta said training covered more than 30 trillion tokens and 200 languages. Those figures and the capability claims below are Meta’s published descriptions, not independent test results. Meta’s Llama 4 announcement
“Open-weight” means model weights are available under stated access terms; it does not mean public domain or unrestricted use. Meta’s current pages list Scout and Maverick, and the download page identifies the Llama 4 Community License Agreement. Review the live license before using or distributing a model. Meta Developer Docs & Resources · Meta Llama 4 download page
Scout vs. Maverick
Both announced models use MoE. In plain terms, only a portion of a model’s parameters is activated for a given token, but the full parameter set still has to be stored. That distinction helps explain why the active-parameter count is far below each model’s total size.
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| Model | Total parameters | Active parameters | Experts | Context and intended use | Compute described at launch |
|---|---|---|---|---|---|
| Scout | 109 billion | 17 billion | 16 | Meta described a 10-million-token context window; positioned for long-context work. | Meta said it could fit on a single NVIDIA H100 GPU with Int4 quantization. |
| Maverick | 400 billion | 17 billion | 128 | Meta positioned it for general assistant and chat use; a context-window figure was not stated in the launch material. | Meta said it could run on one H100 host. |
All figures and deployment descriptions in the table are Meta’s launch claims. A model’s active parameter count is not the same as the hardware memory needed to host it: local deployment must accommodate the full weights, and actual requirements also depend on quantization, runtime, and workload. Meta’s one-GPU and one-host statements should not be read as universal performance guarantees.
What Scout and Maverick are designed to do
Scout: long-context workloads
Scout’s defining launch feature was Meta’s claimed 10-million-token context window. A larger context can let a model process more material in one request, which may help with long documents or large collections of text. The number is Meta’s stated capability; it does not by itself establish how accurately Scout handles every long input or what a particular deployment can support.
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Maverick: general assistant and chat
Maverick has the same stated 17 billion active parameters as Scout but a much larger total model and more experts. Meta presented it as a general-purpose assistant and chat model. Its larger total size affects the weight storage needed even though the active-parameter figure matches Scout’s.
What “natively multimodal” means here
Meta said Llama 4 uses early fusion of text and vision input and was trained on text, image, and video data. In practical terms, the models were designed to work with more than text alone. The announcement’s descriptions establish Meta’s intended capabilities; they are not a substitute for task-specific evaluation, and Meta’s benchmark rankings should be treated as vendor-reported claims rather than independently verified results.
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Behemoth: what was known at launch
Behemoth was a preview, not one of the two models released in the April 5, 2025 announcement. Meta described it as a multimodal MoE teacher model with 288 billion active parameters, 16 experts, and nearly two trillion total parameters, and said it was still training and would not be released yet. That is Behemoth’s status in the 2025 announcement; those historical details do not establish whether it has since been released. Meta’s April 5, 2025 announcement
Are Llama 4 and Meta AI the same thing?
No. Scout and Maverick are model weights developers can access through Meta’s channels and partners, subject to the applicable license. Meta AI is a consumer-facing service and app, not another name for those downloadable model weights. Meta’s April 8, 2026 Muse Spark announcement describes the first Muse-family model as available on meta.ai and in the Meta AI app; that later product announcement does not say Scout or Maverick were discontinued. Meta’s Muse Spark announcement
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Where to access Scout and Maverick
At launch, Meta said the weights could be downloaded from llama.com and Hugging Face, with partner availability expected to follow. Meta’s current developer resources and Llama 4 page provide its access routes and license information. Availability and hosting terms can vary by provider, so check the relevant live listing and license before deploying.
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