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Model details

qwen2.5-vl-72b-instruct

Qwen2.5-VL 72B Instruct is part of Alibaba Cloud's Qwen2.5-VL family, a suite of large multimodal generative models developed by the Qwen team that unifies vision and language understanding in a single system. The 72-billion-parameter configuration succeeds the earlier Qwen2-VL generation and is presented as a foundation model for multimodal tasks, drawing on architectural and training enhancements described in the Qwen2.5-VL Technical Report and accompanying blog post. It is released under the Qwen Research License, reflecting Alibaba's stated intent to keep advanced visual-language research accessible while retaining specific usage terms for the weights.

In practical use, Qwen2.5-VL 72B Instruct is aimed at workflows that need joint reasoning over images and text, including image and video comprehension, document parsing, object grounding, structured data extraction, and visual-agent interactions. The model accepts image and text inputs and produces text outputs, making it well suited for tasks such as analyzing screenshots, interpreting charts and diagrams, extracting fields from forms, and grounding natural-language references to specific regions in a picture. As the largest configuration in the Qwen2.5-VL lineup, it is positioned for users who need stronger multimodal reasoning than smaller variants in the family, while remaining focused on the same core capability of turning visual inputs into reliable, language-grounded responses.

Cortecsqwen2.5-vl-72b-instruct

Quick Info

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Provider
Cortecs
Model key
qwen2.5-vl-72b-instruct
Release date
Jan 27, 2025
Last updated
Jan 27, 2025
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$1.014
Output token cost
$1.014

Limits

Output tokens
32,000 tokens
Context window
32,000 tokens

Latest news about qwen2.5-vl-72b-instruct

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CoverageBenchmark

An aggregated benchmark scorecard on llm-stats.com profiles Qwen2.5-VL-72B-Instruct and ranks the model #250 overall on its composite LLM Stats Score (last updated Wed Sep 16 2026). The page reports concrete multimodal benchmark results sourced to the model's Hugging Face scorecard, including a rank-1 score of 0.96/1 o Capability-tier breakdowns place Qwen2.5-VL-72B-Instruct at 78/119 in Long Context, 130/208 in Vision, 147/244 in Healthcare, 241/363 in Reasoning, and 263/327 in Math, giving developers a snapshot of where the model lands relative to peers across tracked categories. The scorecard does not mention Cortecs as a serving

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