---
title: "Run OpenAI's gpt-oss locally in 5 mins (Beginner Guide)"
description: "Complete 5-minute beginner guide to running OpenAI's gpt-oss locally. Step-by-step setup with Jan AI for private, offline AI conversations."
tags: OpenAI, gpt-oss, local AI, Jan, privacy, Apache-2.0, llama.cpp, Ollama, LM Studio
categories: guides
date: 2025-08-06
ogImage: assets/gpt-oss%20locally.jpeg   
twitter:
  card: summary_large_image
  site: "@jandotai"
  title: "Run OpenAI's gpt-oss Locally in 5 Minutes (Beginner Guide)"
  description: "Complete 5-minute beginner guide to running OpenAI's gpt-oss locally with Jan AI for private, offline conversations."
  image: assets/gpt-oss%20locally.jpeg
---
import { Callout } from 'nextra/components'
import CTABlog from '@/components/Blog/CTA'

# Run OpenAI's gpt-oss Locally in 5 mins

![gpt-oss running locally in Jan interface](./_assets/gpt-oss%20locally.jpeg)

OpenAI launched [gpt-oss](https://openai.com/index/introducing-gpt-oss/), marking their return to open-source AI after GPT-2. This model is designed to run locally on consumer hardware. This guide shows you how to install and run gpt-oss on your computer for private, offline AI conversations.

## What is gpt-oss?

gpt-oss is OpenAI's open-source large language model, released under the Apache-2.0 license. Unlike ChatGPT, gpt-oss:

- Runs completely offline - No internet required after setup
- 100% private - Your conversations never leave your device  
- Unlimited usage - No token limits or rate limiting
- Free forever - No subscription fees
- Commercial use allowed - Apache-2.0 license permits business use

Running AI models locally means everything happens on your own hardware, giving you complete control over your data and conversations.

## gpt-oss System Requirements

| Component | Minimum | Recommended |
|-----------|---------|-------------|
| **RAM** | 16 GB | 32 GB+ |
| **Storage** | 11+ GB free | 25 GB+ free |
| **CPU** | 4 cores | 8+ cores |
| **GPU** | Optional | Modern GPU with 6GB+ VRAM recommended |
| **OS** | Windows 10+, macOS 11+, Linux | Latest versions |

**Installation apps available:**
- **Jan** (Recommended - easiest setup) 
- **llama.cpp** (Command line)
- **Ollama** (Docker-based)
- **LM Studio** (GUI alternative)

## How to install gpt-oss locally with Jan (5 mins)

### Step 1: Download Jan

First download Jan to run gpt-oss locally: [Download Jan AI](https://jan.ai/)

<Callout type="info">
Jan is the simplest way to run AI models locally. It automatically handles CPU/GPU optimization, provides a clean chat interface, and requires zero technical knowledge.
</Callout>

### Step 2: Install gpt-oss Model (2-3 minutes)

![Jan Hub showing gpt-oss model in the hub](./_assets/jan%20hub%20gpt-oss%20locally.jpeg)

1. Open Jan Hub -> search "gpt-oss" (it appears at the top)
2. Click Download and wait for completion (~11GB download)
3. Installation is automatic - Jan handles everything

### Step 3: Start using gpt-oss offline (30 seconds)

![Jan interface with gpt-oss model selected and ready to chat](./_assets/jan%20gpt-oss.jpeg)

1. Go to New Chat → select gpt-oss-20b from model picker
2. Start chatting - Jan automatically optimizes for your hardware
3. You're done! Your AI conversations now stay completely private

Success: Your gpt-oss setup is complete. No internet required for chatting, unlimited usage, zero subscription fees.

## Jan with gpt-oss vs ChatGPT vs other Local AI Models

| Feature | gpt-oss (Local) | ChatGPT Plus | Claude Pro | Other Local Models |
|---------|----------------|--------------|------------|-------------------|
| Cost | Free forever | $20/month | $20/month | Free |
| Privacy | 100% private | Data sent to OpenAI | Data sent to Anthropic | 100% private |
| Internet | Offline after setup | Requires internet | Requires internet | Offline |
| Usage limits | Unlimited | Rate limited | Rate limited | Unlimited |
| Performance | Good (hardware dependent) | Excellent | Excellent | Varies |
| Setup difficulty | Easy with Jan | None | None | Varies |

## Alternative Installation Methods

### Option 1: Jan (Recommended)

- Best for: Complete beginners, users wanting GUI interface
- Setup time: 5 minutes
- Difficulty: Very Easy

Already covered above - [Download Jan](https://jan.ai/)

### Option 2: llama.cpp (Command Line)

- Best for: Developers, terminal users, custom integrations  
- Setup time: 10-15 minutes  
- Difficulty: Intermediate

```bash
# macOS
brew install llama-cpp

# Windows: grab Windows exe from releases
curl -L -o gpt-oss-20b.gguf https://huggingface.co/openai/gpt-oss-20b-gguf/resolve/main/gpt-oss-20b.gguf
./main -m gpt-oss-20b.gguf --chat-simple

# Add GPU acceleration (adjust -ngl value based on your GPU VRAM)
./main -m gpt-oss-20b.gguf --chat-simple -ngl 20
```

### Option 3: Ollama (Docker-Based)

Best for: Docker users, server deployments  
Setup time: 5-10 minutes  
Difficulty: Intermediate

```bash
# Install from https://ollama.com
ollama run gpt-oss:20b
```

### Option 4: LM Studio (GUI Alternative)

Best for: Users wanting GUI but not Jan  
Setup time: 10 minutes  
Difficulty: Easy

1. Download LM Studio from official website
2. Go to Models → search "gpt-oss-20b (GGUF)"
3. Download the model (wait for completion)
4. Go to Chat tab → select the model and start chatting

## gpt-oss Performance & Troubleshooting

### Expected Performance Benchmarks

| Hardware Setup | First Response | Subsequent Responses | Tokens/Second |
|---------------|---------------|---------------------|---------------|
| **16GB RAM + CPU only** | 30-45 seconds | 3-6 seconds | 3-8 tokens/sec |
| **32GB RAM + RTX 3060** | 15-25 seconds | 1-3 seconds | 15-25 tokens/sec |
| **32GB RAM + RTX 4080+** | 8-15 seconds | 1-2 seconds | 25-45 tokens/sec |

### Common Issues & Solutions

Performance optimization tips:
- First response is slow: Normal - kernels compile once, then speed up dramatically
- Out of VRAM error: Reduce context length in settings or switch to CPU mode
- Out of memory: Close memory-heavy apps (Chrome, games, video editors)
- Slow responses: Check if other apps are using GPU/CPU heavily

Quick fixes:
1. Restart Jan if responses become slow
2. Lower context window from 4096 to 2048 tokens
3. Enable CPU mode if GPU issues persist
4. Free up RAM by closing unused applications

## Frequently Asked Questions (FAQ)

### Is gpt-oss completely free?
Yes! gpt-oss is 100% free under Apache-2.0 license. No subscription fees, no token limits, no hidden costs.

### How much internet data does gpt-oss use?
Only for the initial 11GB download. After installation, gpt-oss works completely offline with zero internet usage.

### Can I use gpt-oss for commercial projects?
Absolutely! The Apache-2.0 license permits commercial use, modification, and distribution.

### Is gpt-oss better than ChatGPT?
gpt-oss offers different advantages: complete privacy, unlimited usage, offline capability, and no costs. ChatGPT may have better performance but requires internet and subscriptions.

### What happens to my conversations with gpt-oss?
Your conversations stay 100% on your device. Nothing is sent to OpenAI, Jan, or any external servers.

### Can I run gpt-oss on a Mac with 8GB RAM?
No, gpt-oss requires minimum 16GB RAM. Consider upgrading your RAM or using cloud-based alternatives.

### How do I update gpt-oss to newer versions?
Jan automatically notifies you of updates. Simply click update in Jan Hub when new versions are available.

## Why Choose gpt-oss Over ChatGPT Plus?

gpt-oss advantages:
- $0/month vs $20/month for ChatGPT Plus
- 100% private - no data leaves your device  
- Unlimited usage - no rate limits or restrictions
- Works offline - no internet required after setup
- Commercial use allowed - build businesses with it

When to choose ChatGPT Plus instead:
- You need the absolute best performance
- You don't want to manage local installation
- You have less than 16GB RAM

## Get started with gpt-oss today

![gpt-oss running locally with complete privacy](./_assets/run%20gpt-oss%20locally%20in%20jan.jpeg)

Ready to try gpt-oss?
- Download Jan: [https://jan.ai/](https://jan.ai/)
- View source code: [https://github.com/menloresearch/jan](https://github.com/menloresearch/jan)
- Need help? Check our [local AI guide](/post/run-ai-models-locally) for beginners

<CTABlog />