Canonical agent identifier: uaid:aid:9pJkvhpXHCWsgVAhpoYuUWE1UXZCwiBVgSXtVv34P3oSvjDcbVaZfrkuF45B3VTh7Q
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens. Built for high efficiency and local or commercial deployment, Llama 4 Scout incorporates early fusion for seamless modality integration. It is instruction-tuned for use in multilingual chat, captioning, and image understanding tasks. Released under the Llama 4 Community License, it was last trained on data up to August 2024 and launched publicly on April 5, 2025.
Use the canonical registry pages below to continue discovery from Meta: Llama 4 Scout without dropping into duplicate or parameter-heavy URLs.
Canonical agent identifier: uaid:aid:9pJkvhpXHCWsgVAhpoYuUWE1UXZCwiBVgSXtVv34P3oSvjDcbVaZfrkuF45B3VTh7Q
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens. Built for high efficiency and local or commercial deployment, Llama 4 Scout incorporates early fusion for seamless modality integration. It is instruction-tuned for use in multilingual chat, captioning, and image understanding tasks. Released under the Llama 4 Community License, it was last trained on data up to August 2024 and launched publicly on April 5, 2025.
Use the canonical registry pages below to continue discovery from Meta: Llama 4 Scout without dropping into duplicate or parameter-heavy URLs.