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Qwen3.5 9b vs YOLO World

Compare Qwen3.5 9b and YOLO World side-by-side.

Compare Qwen3.5 9b vs YOLO World live

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Models in this comparison

Tencent

Qwen3.5 9b vs YOLO World: Overview

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.

YOLO World

YOLO-World v2 Small (YOLO-World-S-v2) is the smallest variant of Tencent AI Lab’s YOLO-World v2 family, released around February 2024 under GPL-v3. With ~13 million parameters, it adopts a prompt-then-detect paradigm using offline vocabularies and is pretrained on large-scale datasets such as Objects365 and GoldG. The model processes image inputs at 640×640 or 1280×1280 resolutions and supports zero-shot open-vocabulary object detection, enabling recognition of novel categories from text prompts without retraining.

Evaluations show competitive results across benchmarks like LVIS and COCO, while maintaining real-time efficiency. On an NVIDIA V100, the small variant reaches ~74 FPS at standard resolutions. Together with larger YOLO-World v2 models, it provides a scalable framework for efficient, open-vocabulary detection across diverse deployment settings.

Qwen3.5 9b vs YOLO World Comparison Table

PropertyQwen3.5 9bYOLO World
OrganizationQwenTencent AI Lab
Categoryopenopen
Modalitymultimodalmultimodal
Release DateMar 2026Feb 2024
Context Window262K13.0M
Parameters9B
LicenseApache 2.0GPL v3
Pricing per 1M tokens
Input $/1M$0.100
Output $/1M$0.150
Vision Tasks
Object DetectionDemo
CaptioningDemo
OCRDemo
Open Vocabulary Object Detection
Phrase Grounding
Vision Language
Visual Question AnsweringDemo
Model Features
Multimodal Vision
LLMs with Vision Capabilities
Real-Time Vision
Zero-shot Detection
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
71.64%
Avg Response Time8.99s
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)