# GPT-OSS — Open-Weight Language Models by OpenAI

> OpenAI's open-weight GPT models (120B and 20B parameters) available for local deployment, fine-tuning, and integration into custom applications.

## Install

Save as a script file and run:

# GPT-OSS — Open-Weight Language Models by OpenAI

## Quick Use
```bash
git clone https://github.com/openai/gpt-oss.git
cd gpt-oss
pip install -r requirements.txt
python generate.py --model gpt-oss-20b --prompt "Hello, world"
```

## Introduction
GPT-OSS is OpenAI's release of open-weight language models in two sizes: a 120B parameter flagship and a 20B parameter efficient variant. These models can be downloaded, run locally, fine-tuned, and deployed without API dependency.

## What GPT-OSS Does
- Provides fully open model weights for local inference
- Offers a 120B model for maximum capability and a 20B model for efficiency
- Supports text generation, instruction following, and code completion
- Enables fine-tuning on custom datasets without API costs
- Integrates with standard inference frameworks like vLLM and TGI

## Architecture Overview
GPT-OSS models use a transformer architecture with grouped-query attention and rotary position embeddings. The 120B model uses a mixture of experts design for efficient inference relative to its parameter count. Weights are distributed in safetensors format compatible with Hugging Face Transformers, vLLM, and llama.cpp (via GGUF conversion).

## Self-Hosting & Configuration
- Download weights from the GitHub releases or Hugging Face Hub
- The 20B model fits on a single GPU with 24 GB VRAM (quantized)
- The 120B model requires multi-GPU setup or quantization to 4-bit
- Runs with vLLM, TGI, or Hugging Face Transformers out of the box
- Tokenizer and chat template are included in the repository

## Key Features
- Open weights with permissive licensing for commercial use
- Two model sizes for different hardware and latency requirements
- Compatible with OpenAI API format for drop-in replacement
- Supports GGUF quantization for CPU and edge deployment
- Fine-tuning scripts included for custom domain adaptation

## Comparison with Similar Tools
- **Llama 3** — Meta's open model; GPT-OSS offers OpenAI's architecture and training approach
- **Mistral** — efficient open models; GPT-OSS provides a larger 120B flagship option
- **Qwen** — Alibaba's open LLM; GPT-OSS benefits from OpenAI's training data pipeline
- **DeepSeek-V3** — strong open model; GPT-OSS integrates natively with OpenAI tooling

## FAQ
**Q: Is GPT-OSS the same as GPT-4 or GPT-5?**
A: No, GPT-OSS is a separate model family designed specifically for open release with its own architecture.

**Q: Can I fine-tune these models?**
A: Yes, fine-tuning scripts and documentation are provided in the repository.

**Q: What is the license?**
A: The models use a permissive license that allows commercial use with attribution.

**Q: How does the 20B model compare to the 120B?**
A: The 20B model is suitable for most tasks; the 120B excels at complex reasoning and long-context generation.

## Sources
- https://github.com/openai/gpt-oss
- https://github.com/openai/gpt-oss/blob/main/README.md

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Source: https://tokrepo.com/en/workflows/asset-851b341d
Author: Script Depot