Llama 4 Scout vs Qwen2.5 VL 7B Instruct
Compare Llama 4 Scout and Qwen2.5 VL 7B Instruct side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Llama 4 Scout vs Qwen2.5 VL 7B Instruct Comparison Table
Evals updated August 14, 2026Pricing updated August 14, 2026
| Property | Llama 4 Scout | Qwen2.5 VL 7B Instruct |
|---|---|---|
| Organization | Meta | Qwen |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Apr 2025 | Jan 2025 |
| Context Window | 10.0M | 33K |
| Parameters | 109B | 7B |
| License | Custom | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | |
| Output $/1M | $0.300 | |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | ||
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Llama 4 Scout vs Qwen2.5 VL 7B Instruct: Overview
Llama 4 Scout, released on April 5, 2025, is one of Meta AI’s first Llama 4 multimodal models, alongside Maverick. It accepts text + image inputs and produces text outputs, with a knowledge cutoff of August 2024. Scout is notable for its extremely large context window of 10 million tokens, making it well-suited for analyzing very long documents, extended conversations, or large codebases.
Architecturally, Scout uses a Mixture-of-Experts (MoE) system with 16 experts, activating ~17B parameters per inference from a pool of ~109B total parameters, balancing capacity with efficiency. It officially supports 12 languages (including English, Arabic, French, Hindi, and Spanish), while offering multimodal reasoning for images (captioning, Q&A, recognition). Meta highlights that Scout can run on a single Nvidia H100 GPU, making it more accessible than larger-scale Llama 4 models. However, its output token limit is far smaller than its 10M input window, image input support is still constrained, and license restrictions apply for large-scale commercial deployments.
Qwen2.5-VL-7B-Instruct is a 7-billion parameter vision-language model from Alibaba’s QwenLM team, released on January 26, 2025 under the Apache 2.0 license. It is the instruction-tuned variant of the 7B scale in the Qwen2.5-VL family, designed to process multimodal inputs such as text, images, charts, documents, and video. The model enables structured outputs—including JSON for structured content and bounding boxes for visual localization. Weights are publicly available on Hugging Face and GitHub, making it suitable for both research and applied multimodal use.
Frequently Asked Questions
Llama 4 Scout is released under Custom, while Qwen2.5 VL 7B Instruct uses Apache 2.0. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.