Claude Haiku 4.5 vs Qwen2.5 VL 7B Instruct
We don't benchmark Claude Haiku 4.5 or Qwen2.5 VL 7B Instruct on Vision Evals. Claude Haiku 4.5 is proprietary under Proprietary: commercial use per vendor terms. Qwen2.5 VL 7B Instruct is open-weight under Apache 2.0: free for commercial use.
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Claude Haiku 4.5 vs Qwen2.5 VL 7B Instruct Comparison Table
Pricing updated November 4, 2026
| Property | Claude Haiku 4.5 | Qwen2.5 VL 7B Instruct |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Oct 2025 | Jan 2025 |
| Context Window | 200K | 33K |
| Parameters | Unknown | 7B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $1.00 | No published price |
| Output $/1M | $5.00 | No published price |
| Vision Tasks | ||
| Captioning | Demo | Supported |
| Classification | Demo | Supported |
| Object Detection | Demo | Supported |
| OCR | Demo | Supported |
| Visual Question Answering | Demo | Supported |
| Model Features | ||
Both support 3 more features | ||
Claude Haiku 4.5 vs Qwen2.5 VL 7B Instruct: Overview
Claude Haiku 4.5 is Anthropic’s lightweight model in the Claude 4.5 series, released in October 2025 under a proprietary license. Designed for speed and cost efficiency, it delivers near-frontier performance while maintaining Anthropic’s AI Safety Level 2 standard. Haiku 4.5 supports both text and multimodal (text and image) inputs, integrates tool use and extended reasoning, and features a 200,000 token context window, making it adept at handling long or complex workflows. Haiku 4.5 is ideal for developers and researchers seeking rapid, cost-effective model calls for analysis, coding, or multimodal understanding.
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.