Meta: Llama 4 Scout
By Meta Llama
Released: 2025-04-05
Meta Llama Llama 4 Scout, developed by Meta, features 17B parameters, MoE architecture and 328k-token context window. 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. Priced affordably at $0.08/1M tokens.
Visit Meta: Llama 4 ScoutAI-Powered
Leverages advanced AI technology to deliver cutting-edge capabilities and results.
Fast & Efficient
Optimized performance ensures quick results without compromising on quality.
Purpose-Built
Specifically designed for llms tasks and workflows.
Meta Llama Model Timeline
164k tokens context
1,049k tokens context
328k tokens context
131k tokens context
131k tokens context
131k tokens context
131k tokens context
131k tokens context
60k tokens context
131k tokens context
33k tokens context
16k tokens context
131k tokens context
10k tokens context
131k tokens context
8k tokens context
8k tokens context
8k tokens context
Specifications
AI Evaluation
Built for deep analytical thinking and multi-step problem solving. Excels at tasks requiring careful logical reasoning and systematic analysis.
Pros
- Budget-friendly at $0.08/1M tokens
- 328k token context window
- Advanced logical reasoning
- Image and visual analysis
Cons
- API integration required
- May need prompt tuning
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