
Alicloud Ai Multimodal Qvq
- 92 installs
- 396 repo stars
- Updated July 18, 2026
- cinience/alicloud-skills
Prepares visual-reasoning requests for Alibaba Cloud Model Studio QVQ models for step-by-step image reasoning, chart analysis, and visually grounded problem solving.
About
Builds visual-reasoning requests against Alibaba Cloud Model Studio QVQ models. A developer uses it for step-by-step image reasoning, chart analysis, and visually grounded problem solving.
- Targets QVQ visual-reasoning models with exact model strings
- Includes py_compile validation and evidence output
Alicloud Ai Multimodal Qvq by the numbers
- 92 all-time installs (skills.sh)
- Ranked #4,715 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 92 |
|---|---|
| repo stars | ★ 396 |
| Last updated | July 18, 2026 |
| Repository | cinience/alicloud-skills ↗ |
What it does
Prepares visual-reasoning requests for Alibaba Cloud Model Studio QVQ models for step-by-step image reasoning, chart analysis, and visually grounded problem solving.
Files
Category: provider
Model Studio QVQ Visual Reasoning
Validation
mkdir -p output/alicloud-ai-multimodal-qvq
python -m py_compile skills/ai/multimodal/alicloud-ai-multimodal-qvq/scripts/prepare_qvq_request.py && echo "py_compile_ok" > output/alicloud-ai-multimodal-qvq/validate.txtPass criteria: command exits 0 and output/alicloud-ai-multimodal-qwen-vqv/validate.txt is generated.
Critical model names
Use one of these exact model strings:
qvq-plusqvq-max
Typical use
- Mathematical reasoning from screenshots
- Diagram and chart reasoning
- Visually grounded multi-step problem solving
Quick start
python skills/ai/multimodal/alicloud-ai-multimodal-qvq/scripts/prepare_qvq_request.py \
--output output/alicloud-ai-multimodal-qvq/request.jsonNotes
- Use
skills/ai/multimodal/alicloud-ai-multimodal-qwen-vl/for standard image understanding. - Use QVQ when the task explicitly needs stronger reasoning over visual evidence.
References
references/sources.md
interface:
display_name: "Alibaba Cloud AI Multimodal QVQ"
short_description: "Visual reasoning with QVQ models"
default_prompt: "Use $alicloud-ai-multimodal-qvq to complete this ai/multimodal visual reasoning task on Alibaba Cloud."
Sources
- https://help.aliyun.com/document_detail/2850932.html
- https://help.aliyun.com/zh/model-studio/newly-released-models
#!/usr/bin/env python3
"""Prepare a minimal request payload for QVQ visual reasoning."""
from __future__ import annotations
import argparse
import json
from pathlib import Path
DEFAULT_PAYLOAD = {
"model": "qvq-plus",
"prompt": "Read the chart carefully and explain the trend.",
"image": "https://example.com/chart.png",
"max_tokens": 1024,
}
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument(
"--output",
default="output/alicloud-ai-multimodal-qvq/request.json",
)
args = parser.parse_args()
output = Path(args.output)
output.parent.mkdir(parents=True, exist_ok=True)
output.write_text(json.dumps(DEFAULT_PAYLOAD, ensure_ascii=False, indent=2), encoding="utf-8")
print(output)
if __name__ == "__main__":
main()