From the model card
Fields below are copied from the tags and counters on the HuggingFace repository Qwen/Qwen3.5-9B at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.
- Publisher (HF namespace)
- Qwen
- Pipeline tag
- image-text-to-text
- Library
- Transformers
- Weight formats
- safetensors
- License tag
apache-2.0— read the license file in the repo before relying on it- Lineage
-
- base model Qwen/Qwen3.5-9B-Base
- fine-tune of Qwen/Qwen3.5-9B-Base
- Downloads (HF counter at last fetch)
- 12,184,741
- Likes (HF counter at last fetch)
- 1,895
- Model card
- https://huggingface.co/Qwen/Qwen3.5-9B
Use cases
- Multimodal conversational AI on single-GPU infrastructure
- Visual reasoning and image-grounded QA tasks
- Document analysis combining OCR-adjacent understanding and text reasoning
- Local VLM deployment for privacy-sensitive image tasks
- Mid-tier production VLM API replacement
Pros
- Apache 2.0 license
- 9B scale provides strong multimodal reasoning for its size
- Part of Qwen3.5 family with consistent updates
- HuggingFace Transformers native compatibility
Cons
- 9B VLM requires 20-24GB VRAM at FP16 for image inputs
- Accuracy gaps vs. 30B+ VLMs on complex multi-image reasoning
- Not yet as widely benchmarked as Qwen2.5-VL-7B at this publish date
- Image input memory overhead varies by resolution — may exceed expected VRAM
- Instruction following on edge cases less reliable than larger models
Tags
transformerssafetensorsqwen3_5image-text-to-textconversationalbase_model:Qwen/Qwen3.5-9B-Basebase_model:finetune:Qwen/Qwen3.5-9B-Baselicense:apache-2.0eval-resultsendpoints_compatibledeploy:sagemakerdeploy:azureregion:us