Can I run gpt-oss-safeguard?

gpt-oss-safeguard system requirements

Memory needed at 4K context, counting model weights, KV cache, compute buffers and runtime overhead. Download sizes come from the official Ollama registry.

Figures marked (est.) approximate the KV cache because this model's architecture details are not published. They are indicative rather than exact.

How to run gpt-oss-safeguard locally

1. 1.Install Ollama for Windows, macOS or Linux.
2. 2.Run this in a terminal:ollama run gpt-oss-safeguard:20b
3. 3.The weights download on first run, then an interactive prompt opens.

Frequently asked questions about gpt-oss-safeguard

How much VRAM do I need to run gpt-oss-safeguard?

At 4K context, the smallest published build of gpt-oss-safeguard (MXFP4) needs roughly 18.8 GB of GPU memory once weights, KV cache, compute buffers and runtime overhead are counted. Bigger quantizations and longer context windows need more. It can also run partly or entirely on the CPU using system RAM, more slowly.

Can I run gpt-oss-safeguard without a dedicated GPU?

Yes, but slowly. Without a GPU the model runs on the CPU using system RAM, which usually means a few tokens per second rather than dozens. You would need at least 18.8 GB of free RAM for the smallest build.

How big is the gpt-oss-safeguard download?

The smallest published build is 12.8 GB. There are 2 builds in total, the largest being 60.9 GB. Leave some extra free disk space beyond the download itself.

How do I run gpt-oss-safeguard locally?

Install Ollama, then run "ollama run gpt-oss-safeguard:20b" in a terminal. The weights download on first use and an interactive session opens.