Qwen3.5 9b vs Qwen3 VL 235B A22B Instruct
Compare Qwen3.5 9b and Qwen3 VL 235B A22B Instruct 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 VL 235B A22B Instruct Comparison Table
Evals updated August 6, 2026Pricing updated August 10, 2026
| Property | Qwen3.5 9b | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Organization | Qwen | Qwen |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Mar 2026 | Sep 2025 |
| Context Window | 262K | 256K |
| Parameters | 9B | 235B |
| License | Apache 2.0 | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | $0.210 |
| Output $/1M | $0.150 | $1.90 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | ||
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| 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 | 65.8% |
| Avg cost / sample | – | $0.0007 |
| Avg speed / sample | – | 9.17s |
| By task | ||
| Object Detection | – | 52.2% $0.0014 |
| Counting | – | 47.3% $0.0002 |
| Identification | – | 90.6% $0.0002 |
| OCR | – | 88.1% $0.0010 |
| Data Extraction | – | 86.6% $0.0002 |
| Reasoning (low) | – | 29.8% $0.0002 |
| Reasoning (high) | – | 33.8% $0.0002 |
Qwen3.5 9b vs Qwen3 VL 235B A22B Instruct: 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.
Qwen3 VL 235B A22B Instruct is a flagship multimodal vision-language model developed by Qwen (Alibaba Cloud), designed for instruction-following tasks that combine advanced text generation with visual understanding. It serves as a high-end open-weight model for developers and researchers building multimodal AI systems that require strong reasoning, perception, and long-context capabilities.
The model supports interleaved text and image inputs, very long context windows (up to roughly 256K tokens), and efficient inference through a mixture-of-experts architecture with about 22B active parameters out of 235B total. In today’s landscape, it competes with top-tier proprietary vision-language models while offering the advantages of open weights and flexible deployment. Typical applications include multimodal assistants, document and image analysis, visual reasoning, and large-context instruction-based workflows.
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.