Claude Opus 4.5 vs Qwen2.5 VL 7B Instruct

Compare Claude Opus 4.5 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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AnthropicClaude Opus 4.5
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QwenQwen2.5 VL 7B Instruct
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Claude Opus 4.5 vs Qwen2.5 VL 7B Instruct: Overview

Claude Opus 4.5

Claude Opus 4.5 is Anthropic’s most advanced large language model in the Claude Opus family, designed for high-end reasoning, coding, and autonomous agent workflows. Released in late 2025, it targets developers and enterprises that need reliable long-context understanding and strong multi-step problem solving in production environments.

The model supports text and code natively, with reported multimodal capabilities for documents and images, and offers an exceptionally large context window of up to roughly 200,000 tokens. Claude Opus 4.5 emphasizes long-horizon task execution, complex code generation and refactoring, and sustained reasoning over large inputs. In the current landscape, it positions itself as a premium, accuracy- and reasoning-focused alternative to faster or cheaper peers, trading cost for depth and contextual fidelity. Typical applications include advanced coding assistants, research analysis, agentic automation, and enterprise knowledge workflows deployed via Anthropic’s API or major cloud platforms.

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.

Claude Opus 4.5 vs Qwen2.5 VL 7B Instruct Comparison Table

PropertyClaude Opus 4.5Qwen2.5 VL 7B Instruct
OrganizationAnthropicQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateNov 2025Jan 2025
Context Window200K33K
Parameters7B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$5.00
Output $/1M$25.00
Vision Tasks
CaptioningDemoDemo
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
ClassificationDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
52.24%
Avg Response Time47.64s
Defect Detection
60%(9/15)
Document Understanding
77.8%(7/9)
Object Counting
0%(0/10)
Object Understanding
57.1%(8/14)
Spatial Understanding
57.9%(11/19)