🚀 50K+ Downloads | OpenAI’s Open-Weight Model | Docker Hub: ai/gpt-oss

What is GPT-OSS?

GPT-OSS is OpenAI’s groundbreaking open-weight model series designed for powerful reasoning, agentic tasks, and versatile developer use cases. As OpenAI’s first open-source offering, GPT-OSS represents a significant shift toward accessible AI development, providing developers with a 20B parameter model optimized for complex reasoning tasks and autonomous agent applications.

Key Technical Specifications

Architecture Overview

• Total Models: 5 variants (all 20B parameters with different quantizations)
• Parameters: 20B (single size, multiple quantizations)
• Context Window: 131K tokens
• License: Open-weight (OpenAI)
• Provider: OpenAI
• Architecture: GPT-OSS (OpenAI transformer)
• Specialization: Reasoning & Agentic Tasks
• Downloads: 50K+

What Makes GPT-OSS Different

# Traditional Closed AI Model
provider = "OpenAI"
model_access = "API-only"
weights = "Closed"
specialization = "General purpose"
reasoning = "Standard"

# GPT-OSS Open Model  
provider = "OpenAI"
model_access = "Full local deployment"    # Revolutionary change
weights = "Open-weight"                   # First from OpenAI
specialization = "Reasoning & Agents"     # Purpose-built
reasoning = "Advanced logical reasoning"  # Enhanced capabilities
context_window = "131K tokens"            # Large context
quantization = "Multiple options"         # Flexible deployment
local_inference = True                    # Complete ownership

What is Docker Model Runner?

Docker Model Runner (DMR) is a tool that makes it easy to manage, run, and deploy AI models using Docker. It allows developers to pull, run, and serve large language models (LLMs) and other AI models directly from Docker Hub or any OCI-compliant registry. DMR integrates with Docker Desktop and Docker Engine, enabling you to serve models via OpenAI-compatible APIs, interact with models from the command line, and manage them through a graphical interface. Models are cached locally after the first pull and are loaded into memory only at runtime to optimize resource usage. DMR supports both command-line and API-based interactions, making it suitable for building generative AI applications, experimenting with ML workflows, or integrating AI into software development pipelines.

Quick Start

# Pull latest model (20B-UD-Q4_K_XL)
docker model pull ai/gpt-oss

All Available Models

# Recommended balanced model
docker model pull ai/gpt-oss:20B-UD-Q4_K_XL  # 11.04GB (recommended)

# Quality vs Size Options
docker model pull ai/gpt-oss:20B-F16         # 12.83GB (highest quality)
docker model pull ai/gpt-oss:20B-UD-Q6_K_XL  # 11.20GB (high quality)
docker model pull ai/gpt-oss:20B-UD-Q8_K_XL  # 12.28GB (near-full precision)

# All variants are 20B parameters with 131K context window
# Choose based on your quality vs storage requirements

Basic Usage Examples

1. Reasoning Tasks

docker model run ai/gpt-oss:20B-UD-Q4_K_XL

> Solve this logic puzzle: If all roses are flowers, and some flowers are red, can we conclude that some roses are red?