Claude Opus 4 vs Qwen2.5 VL 7B Instruct
Compare Claude Opus 4 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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Claude Opus 4 is deprecated and can no longer be run. Details and evals are still available on its model page.
Models in this comparison
Claude Opus 4 vs Qwen2.5 VL 7B Instruct: Overview
Claude 4 Opus, released by Anthropic in May 2025, is the flagship model of the Claude 4 family, built for complex, long-horizon reasoning and advanced coding workflows. It is multimodal, supporting text (including voice), images, and tool use, and operates as a hybrid reasoning model—able to deliver quick answers in fast mode or switch to extended thinking for deeper, multi-step problem solving. With a ~200,000-token context window and a training cutoff around March 2025, it is optimized for handling large documents, long conversations, and sophisticated agentic tasks.
Positioned at the high end of Anthropic’s offerings, Opus 4 achieves state-of-the-art results on coding benchmarks like SWE-Bench (72.5%) and Terminal-Bench (43.2%). It is best suited for research, enterprise automation, and software development at scale. The model is classified at Anthropic’s ASL-3 safety level, denoting advanced oversight and safety features.
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 vs Qwen2.5 VL 7B Instruct Comparison Table
| Property | Claude Opus 4 | Qwen2.5 VL 7B Instruct |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | May 2025 | Jan 2025 |
| Context Window | 200K | 33K |
| Parameters | 7B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $15.00 | |
| Output $/1M | $75.00 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Object Detection | ||
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Classification | ||
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Foundation Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 56.72% | 52.24% |
| Avg Response Time | 19.74s | 47.64s |
| Defect Detection | 66.7%(10/15) | 60%(9/15) |
| Document Understanding | 88.9%(8/9) | 77.8%(7/9) |
| Object Counting | 0%(0/10) | 0%(0/10) |
| Object Understanding | 64.3%(9/14) | 57.1%(8/14) |
| Spatial Understanding | 57.9%(11/19) | 57.9%(11/19) |