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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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QwenQwen2.5 VL 7B Instruct
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QwenQwen3.5 9b
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Qwen2.5 VL 7B Instruct vs Qwen3.5 9b Comparison Table

Evals updated October 8, 2026Pricing updated October 11, 2026

PropertyQwen2.5 VL 7B InstructQwen3.5 9b
OrganizationQwenQwen
Categoryopenopen
Modalitymultimodalmultimodal
Release DateJan 2025Mar 2026
Context Window33K262K
Parameters7B9B
LicenseApache 2.0Apache 2.0
Pricing per 1M tokens
Input $/1MNo published price$0.100
Output $/1MNo published price$0.150
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationSupportedSupported
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionSupportedSupported
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks
OverallNot evaluated
56.0%
4/5 tasks
Quantizationsself-hosted
BF1656.0%FP854.8%AWQ-INT457.4%hardware →
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
$0
Counting–
56.8%
±1.4, Mean of 3 runs, range 55.4 to 58.1
$0
Identification–
83.3%
±1.6, Mean of 3 runs, range 81.3 to 84.4
$0
OCR––
by category
Reasoning–
45.9%
±1.7, Mean of 3 runs, range 44.4 to 47.7
$0

Qwen2.5 VL 7B Instruct vs Qwen3.5 9b: Overview

Qwen2.5 VL 7B Instruct

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

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.