Qwen2.5 VL 7B Instruct vs Qwen3.5 9b
Compare Qwen2.5 VL 7B Instruct and Qwen3.5 9b side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.
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Qwen2.5 VL 7B Instruct vs Qwen3.5 9b Comparison Table
Evals updated October 8, 2026Pricing updated October 11, 2026
| Property | Qwen2.5 VL 7B Instruct | Qwen3.5 9b |
|---|---|---|
| Organization | Qwen | Qwen |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Jan 2025 | Mar 2026 |
| Context Window | 33K | 262K |
| Parameters | 7B | 9B |
| License | Apache 2.0 | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | No published price | $0.100 |
| Output $/1M | No published price | $0.150 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | Supported | Supported |
| Classification | Supported | Supported |
| Document Question Answering | Supported | Supported |
| Image Tagging | Supported | Supported |
| Multi-Label Classification | Supported | Supported |
| Object Detection | Supported | Supported |
| OCR | Demo | Demo |
| Vision Language | Supported | Supported |
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Supported |
| Multimodal Vision | Supported | Supported |
Vision Evalsground-truth scores across 5 vision tasks | ||
| Overall | Not evaluated | 56.0% 4/5 tasks |
| Quantizationsself-hosted | ||
| Avg cost / sample | – | $0.0021 |
| Avg speed / sample | – | 41.36s |
| By task | ||
| Object Detection | – | 38.1% ±5.7, Mean of 3 runs, range 33.5 to 44.9 |
| Counting | – | 56.8% ±1.4, Mean of 3 runs, range 55.4 to 58.1 |
| Identification | – | 83.3% ±1.6, Mean of 3 runs, range 81.3 to 84.4 |
| OCR | – | – |
| by category | ||
| Reasoning | – | 45.9% ±1.7, Mean of 3 runs, range 44.4 to 47.7 |
Qwen2.5 VL 7B Instruct vs Qwen3.5 9b: Overview
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.
Qwen3.5-9B is a 9-billion-parameter multimodal foundation model developed by Alibaba Cloud's Qwen team, released on March 2, 2026 as part of the Qwen3.5 model family. Designed for efficient multimodal reasoning and long-context language tasks, it notably outperforms the older Qwen3-30B, a model more than three times its size, on key benchmarks including GPQA Diamond, IFEval, and LongBench.
The model supports vision-language inputs through an early-fusion multimodal architecture built on a dense hybrid foundation of Gated Delta Networks and Gated Attention. It can also operate in a text-only mode by skipping the vision encoder during inference. It provides a 262,144-token context window (extensible to ~1M tokens via YaRN) and is released under the Apache License 2.0. Within the current AI landscape, Qwen3.5-9B offers a strong balance of capability and efficiency, making it well-suited for multimodal assistants, document analysis, long-context reasoning, and developer-deployed agentic systems.
Frequently Asked Questions
Qwen2.5 VL 7B Instruct has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.
Yes. The comparison demo on this page runs both models on the same image side by side for open prompts and image captioning in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.