Deploy Qwen3.5-4B-GGUF on Copilot+ PC Uncensored Edition Step-by-Step

Deploying this model locally is quickest when done via a simple curl command.

Simply follow the directions outlined below.

The installer auto-downloads and deploys the entire model pack.

The configuration wizard runs silently to set up the model for peak performance.

📘 Build Hash: 3195d0e84079eb641262437301599e3d • 🗓 2026-07-02



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: enough space for background apps and OS overhead
  • Storage: extra room for future model updates and datasets
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The **Qwen3.5-4B-GGUF** model delivers strong performance for a range of natural language tasks while maintaining a compact footprint. Built with 4B parameters and optimized for the GGUF quantization format, it balances speed and accuracy for both research and production environments. It supports a context window of up to 8192 tokens, enabling detailed reasoning and multi‑step problem solving without sacrificing latency. Benchmarks show the model achieves competitive perplexity scores on standard benchmarks while consuming less than 5 GB of GPU memory during inference. The integrated

below provides a quick comparison with similar open‑source models, highlighting its efficiency and ease of deployment.

Parameters 4 B
Context Length 8192 tokens
Quantization GGUF
Memory Usage (inference) <5 GB
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