---
title: Roy-DOU/WebCoder-27B
url: https://recentmodel.com/models/Roy-DOU/WebCoder-27B/
status: just landed · new, unvetted
published: 2026-10-16T07:05:31Z
updated: 2026-10-24T11:24:09Z
source: https://huggingface.co/Roy-DOU/WebCoder-27B
---

# Roy-DOU/WebCoder-27B

WebCoder-27B is a general frontend development agent, trained from Qwen3.8-27B with artifact-grounded agentic reinforcement learning. Dense, 28B params. Context: 256K tokens (config). License: apache-2.0.


- **Org:** Roy-DOU
- **Released:** 2026-10-16
- **Status:** just landed · new, unvetted
- **License:** apache-2.0 (permissive)
- **Parameters:** 27.8B
- **Architecture:** dense · Qwen3_5ForConditionalGeneration
- **Context:** 262,144 tokens
- **Task:** image-text-to-text · vision
- **Signal:** 2 HF likes · 10 downloads

## Runs on

real quant files; sizing calculation, not tested.

- Q4 ~19.9 GB: 24GB GPU (3090 / 4090), 32GB GPU (5090), 24GB GPU (7900 XTX), Mac 36GB, CPU only, 32GB RAM (slow)
- Q8 ~32.8 GB: 48GB GPU (RTX 6000 Ada / A6000), Mac 48GB, Mac 64GB (M1 Max), CPU only, 64GB RAM (slow)
- FP16 ~58.7 GB: 96GB GPU (RTX Pro 6000 Blackwell), 1× DGX Spark (128GB), 2× DGX Spark (256GB), Strix Halo 128GB unified (~96GB usable), Mac 96GB, Mac 128GB, Mac 192GB, Mac 256GB, Mac 512GB, CPU only, 128GB RAM (slow), CPU only, 256GB RAM (slow)

## Links

- [Hugging Face](https://huggingface.co/Roy-DOU/WebCoder-27B)