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: 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.
Qwen3.5 9b vs Qwen3 VL 235B A22B Instruct Comparison Table
| 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 | $0.200 |
| Output $/1M | $0.150 | $0.880 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Object Detection | ||
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Overall Score | 71.64% | |
| Avg Response Time | 8.99s | |
| Defect Detection | 86.7%(13/15) | |
| Document Understanding | 66.7%(6/9) | |
| Object Counting | 30%(3/10) | |
| Object Understanding | 71.4%(10/14) | |
| Spatial Understanding | 84.2%(16/19) | |