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Llama 4 Maverick vs Qwen2.5 VL 7B Instruct

Compare Llama 4 Maverick 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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MetaLlama 4 Maverick
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QwenQwen2.5 VL 7B Instruct
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Llama 4 Maverick vs Qwen2.5 VL 7B Instruct Comparison Table

Evals updated July 10, 2026Pricing updated July 16, 2026

PropertyLlama 4 MaverickQwen2.5 VL 7B Instruct
OrganizationMetaQwen
Categoryopenopen
Modalitymultimodalmultimodal
Release DateApr 2025Jan 2025
Context Window1.0M33K
Parameters400B7B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$0.200
Output $/1M$0.800
Vision Tasks
CaptioningDemoDemo
Object Detection
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision

Llama 4 Maverick vs Qwen2.5 VL 7B Instruct: Overview

Llama 4 Maverick

Llama 4 Maverick, introduced on April 5, 2025, is one of the first models in Meta’s Llama 4 family, designed as a natively multimodal model supporting text + image inputs with text outputs. It employs a Mixture-of-Experts (MoE) architecture with 128 experts, activating ~17B parameters per token out of a pool of ~400B total parameters. This design improves scalability, efficiency, and reasoning capacity. Maverick has a 1M-token context window, enabling it to handle large documents, extended conversations, and multimodal reasoning. Its knowledge cutoff is August 2024.

The model is released under the Llama 4 Community License and comes in both base and instruction-tuned (“Instruct”) versions. Maverick is widely deployed via Hugging Face, Google Vertex AI, Amazon Bedrock, and Oracle Cloud, making it one of the most accessible large open-weight models. However, it outputs text only (no image/audio generation) and, while input capacity is huge, output limits are typically much smaller. The MoE design also raises hardware demands, as maintaining 128 experts requires significant compute resources, and Meta’s license introduces restrictions around commercial-scale use.

Qwen2.5 VL 7B Instruct

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.