Run gpt-oss-20b Windows 11 For Low VRAM (6GB/8GB) No-Code Guide

Run gpt-oss-20b Windows 11 For Low VRAM (6GB/8GB) No-Code Guide

Docker offers the quickest path to setting up this model locally.

Follow the guidelines below to continue.

Finishing these instructions ensures you instantly get all the exact results you wanted to receive.

🗂 Hash: ab4123137a0fd9d327d22903924eb5abLast Updated: 2026-06-22



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

The gpt-oss-20b model represents a significant step forward in open‑source large language models, offering a balanced blend of capability and accessibility for developers and researchers. Built with 20 billion parameters, it delivers strong performance on a wide range of NLP tasks while remaining lightweight enough for deployment on standard hardware. Its state‑of‑the‑art architecture incorporates advanced attention mechanisms and efficient memory usage, enabling context lengths up to 8K tokens without significant latency. The model has been trained on a diverse corpus of publicly available web data and scholarly sources, ensuring broad factual knowledge and multilingual support. Below is a quick overview of its key technical specifications, presented in a concise table for easy reference.

Parameters 20 billion
Context Length 8K tokens
Training Data Public web & scholarly sources
License Open source
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