llama-4-scout by deepinfra - AI Model Details, Pricing, and Performance Metrics
llama-4-scout
completionsLlama 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.
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.
Access llama-4-scout through LangDB AI Gateway
Integrate with meta's llama-4-scout and 250+ other models through a unified API. Monitor usage, control costs, and enhance security.
Free tier available • No credit card required
Category Scores
Benchmark Tests
| Metric | HLE | AIME | GPQA | MMLU | MMMU | SciCode | MATH-500 | MMLU-Pro | LiveCodeBench | AA Math Index | AA Coding Index | AAII |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Score | 4.3 | 28.3 | 57.9 | 79.6 | 69.4 | 17.0 | 84.4 | 74.8 | 29.9 | 14.0 | 16.1 | 28.1 |
Compare with Similar Models
Code Examples
Integration samples and API usage
Related Models
Similar models from deepinfra