Qwen3.5 9b vs Qwen3.7 Plus
Compare Qwen3.5 9b and Qwen3.7 Plus side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Qwen3.5 9b vs Qwen3.7 Plus Comparison Table
Evals updated August 20, 2026Pricing updated August 24, 2026
| Property | Qwen3.5 9b | Qwen3.7 Plus |
|---|---|---|
| Organization | Qwen | Qwen |
| Category | open | closed |
| Modality | multimodal | — |
| Release Date | Mar 2026 | — |
| Context Window | 262K | — |
| Parameters | 9B | |
| License | Apache 2.0 | |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | $0.320 |
| Output $/1M | $0.150 | $1.28 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Vision Language | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 67.4% |
| Avg cost / sample | – | $0.0008 |
| Avg speed / sample | – | 7.01s |
| By task | ||
| Object Detection | – | 60.1% $0.0013 |
| Counting | – | 50.0% $0.0004 |
| Identification | – | 84.4% $0.0003 |
| OCR | – | 86.5% $0.0009 |
| Data Extraction | – | 83.5% $0.0004 |
| Reasoning (low) | – | 39.7% $0.0003 |
| Reasoning (high) | – | 68.2% $0.0043 |
Qwen3.5 9b vs Qwen3.7 Plus: Overview
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
Qwen3.5 9b 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 image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.