microsoft/AesCode-8B
image-text-to-text model by microsoft
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Model card & documentation
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AesCode generates information-rich visual artifacts such as slides, posters, and dashboards as HTML/CSS. The output remains structured, editable, and verifiable, but the task poses a distinct challenge: code models cannot see how layout, hierarchy, and color come together on the canvas. Image generators offer the opposite strength. They compose visually compelling pages but often misrender text, numbers, and logical relationships. AesCode uses an image generated from the same prompt as an aesthetic reference while following the prompt for the required content. Reference input alone does not solve the problem. Off-the-shelf vision-language models may copy hallucinated content or ignore the reference layout. AesCode separates semantic requirements from visual cues through graph-structured supervision and decoupled cross-modal rewards. AesCode-8B starts from Qwen3-VL-8B-Instruct and is trained with cold-start SFT followed by GDPO across seven reward channels. AesCode is designed to generate information-rich visual artifacts as structured HTML/CSS. It is suited for creating editable slides,…
Read the full model card ↗ · Preview checked 2026-10-31T09:41:24.875Z
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Model overview
microsoft/AesCode-8B is a image-text-to-text model repository published by microsoft on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- transformers
- Recent downloads (30 days)
- 735
- Cumulative likes
- 72
- Hugging Face trending score
- 68
- Reported safetensors parameters
- 8,767,123,696
- Architecture
- Qwen3VLForConditionalGeneration
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-29T13:04:44.000Z
- Last modified
- 2026-10-14T19:28:35.000Z
Compatibility and lineage
Reported languages: en
Reported base models: Qwen/Qwen3-VL-8B-Instruct
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-18T06:42:00.150Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.