Qwen3-VL-4B-Thinking
is a 4-billion-parameter multimodal large language model from the Qwen team at Alibaba Cloud.
Part of the
Qwen3-VL
(Vision-Language) family, it is designed for advanced visual reasoning and chain-of-thought generation across image, text, and video inputs.
Compared to the
Instruct
variant, the
Thinking
model emphasizes deeper multi-step reasoning, analysis, and planning. It produces detailed, structured outputs that reflect intermediate reasoning steps, making it well-suited for research, multimodal understanding, and agentic workflows.
Features
Vision-Language Understanding
: Processes images, text, and videos for joint reasoning tasks.
Structured Thinking Mode
: Generates intermediate reasoning traces for better transparency and interpretability.
High Accuracy on Visual QA
: Performs strongly on visual question answering, chart reasoning, and document analysis benchmarks.
Multilingual Support
: Understands and responds in multiple languages.
Optimized for Efficiency
: Delivers strong performance at 4B scale for on-device or edge deployment.
Use Cases
Multimodal reasoning and visual question answering
Scientific and analytical reasoning tasks involving charts, tables, and documents
Step-by-step visual explanation or tutoring
Research on interpretability and chain-of-thought modeling
Integration into agent systems that require structured reasoning
Inputs and Outputs
Input:
Text, images, or combined multimodal prompts (e.g., image + question)
Output:
Generated text, reasoning traces, or structured responses
May include explicit thought steps or structured JSON reasoning sequences
Runs of NexaAI qwen3vl-4B-Thinking-4bit-mlx on huggingface.co
5
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs
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