Meta: Llama 4 Scout
Provided by OpenRouter
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.
Specifications
327,680 tokens$0.080/M$0.300/MAbout Meta: Llama 4 Scout
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.
Strengths
- •Multimodal understanding - can process text and images
- •Large context window (328k tokens) for long conversations
Use Cases
- •Image and document understanding
- •Content creation and writing assistance
- •General conversations and Q&A
Limitations
Performance may vary based on query complexity, context length, and task type. Consider using higher-tier models for production-critical applications.
Sample Prompts
Try these prompts to explore Meta: Llama 4 Scout's capabilities:
Analyze this image and describe what you see in detail
Extract the key information from this screenshot
Compare the two images and explain the differences
Tip: Customize these prompts to fit your specific needs and use cases.
Premium Model
This model requires credits to use. Meta: Llama 4 Scout offers advanced capabilities and high-performance features for production-grade applications.
Credits required for premium models. Free models are available without credits.
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