OpenAI Releases gpt-oss Models for Local Use: Run Advanced AI on Your Own Hardware

OpenAI has just reshaped the AI landscape—again. On August 5, 2025, the company unveiled its first open-weight models in six years: gpt-oss-120b and gpt-oss-20b. Unlike their powerful cloud-based GPT-4o or GPT-5 siblings, these new models can be downloaded and run locally, giving developers, researchers, and enterprises full control over performance, security, and customization.

The gpt-oss models arrive at a time when many organizations are seeking alternatives to cloud-based AI to minimize latency, increase data privacy, and tailor AI behaviors to specific tasks. These new models mark a turning point in accessibility and innovation, with open-source licensing under Apache 2.0—a rare move from OpenAI since GPT-2’s release in 2019.

What is gpt-oss and How Can It Benefit Your Workflow?

The term “gpt-oss” refers to OpenAI’s new open-weight AI models: gpt-oss-20b and gpt-oss-120b. These transformer-based models are designed for local execution, offering a powerful yet flexible alternative to proprietary AI models hosted in the cloud.

Key features include:

• Mixture-of-Experts (MoE) architecture, reducing compute load per token

• Configurable Chain-of-Thought (CoT) settings: low, medium, or high for balancing performance and cost

• 128K token context window, enabling long-form tasks like document summarization or code analysis

• Run locally on consumer or enterprise hardware, with memory requirements starting at 16GB

The gpt-oss-20b model boasts 21 billion parameters, with only 3.6 billion used per token thanks to MoE—making it manageable for high-end personal devices. The gpt-oss-120b, however, demands 80GB of memory, making it ideal for advanced GPUs like the Nvidia H100.

This dual-model strategy means OpenAI is targeting both individual users and large organizations with a single, open-source release.

Best Practices for Running gpt-oss Models on Local Hardware

To effectively deploy gpt-oss, it’s essential to match the model with your hardware capabilities. Here’s a breakdown of what’s required:

• gpt-oss-20b: Works on devices with 16GB RAM and modern CPUs or consumer GPUs. Ideal for developers and smaller-scale inference.

• gpt-oss-120b: Requires high-performance AI accelerators (e.g., Nvidia H100) or clusters. Best for enterprises and research institutions.

Performance-wise, OpenAI reports that gpt-oss-120b rivals proprietary models like GPT-3.5 (o3) and outpaces mini variants of GPT-4 (o4-mini) in many benchmarks, especially in coding and math. However, it still lags behind state-of-the-art in general knowledge exams like Humanity’s Last Exam, where o3 scores 24.9% with tools compared to 19% for gpt-oss-120b.

Both models lack multimodal capabilities (i.e., no image or audio input/output), keeping them strictly text-based for now.

Why OpenAI Made gpt-oss Open Source in 2025

This move aligns with rising demand for AI sovereignty, where companies wish to manage their AI systems in-house for privacy, compliance, or control reasons. According to OpenAI, many users have already been mixing cloud GPT APIs with third-party open models like LLaMA or Mistral to achieve this balance.

By launching gpt-oss, OpenAI hopes to capture that hybrid use case entirely within its own ecosystem.

The models are also meant to serve developer communities interested in fine-tuning models for niche applications—from healthcare assistants to legal tech tools—without reliance on proprietary platforms. And thanks to Apache 2.0 licensing, developers can modify and distribute their versions without fear of legal backlash.

How Safe Are the gpt-oss Models?

Security was a top concern. OpenAI developers attempted to force malicious behavior in “worst-case” tests using adversarial fine-tuning. Despite this, gpt-oss models struggled to perform harmful tasks effectively.

This result reinforces OpenAI’s Preparedness Framework, which includes deliberative alignment, system prompt hierarchies, and robust safety layers—even in open models.

In essence, OpenAI believes gpt-oss cannot easily be used for evil, which is likely a key reason they felt confident releasing it publicly.

A New Era of Decentralized AI Begins

The release of gpt-oss-120b and gpt-oss-20b marks a bold return to open AI infrastructure by OpenAI. With transparent licensing, robust safety mechanisms, and compatibility across hardware scales, the models offer a compelling path forward for anyone seeking more control and agility in how they use AI.

Whether you’re an AI developer, enterprise team, or independent researcher, gpt-oss might be your entry point into high-performance, locally run generative AI—without the cloud dependency.

You Must Know:

What hardware do you need to run gpt-oss-120b?
You’ll need at least 80GB of memory and an AI accelerator like Nvidia H100 to run gpt-oss-120b efficiently.

Is gpt-oss better than GPT-4?
Not exactly. While gpt-oss-120b performs near GPT-3.5 (o3) levels, it doesn’t surpass GPT-4 in general reasoning, knowledge, or language comprehension.

Is gpt-oss open-source?
Yes, both models are released under the Apache 2.0 license, allowing full use, modification, and redistribution.

Does gpt-oss support multimodal input?
No. Both models are text-only out of the box and do not natively support images, audio, or video.

Can gpt-oss be fine-tuned for specific tasks?
Yes. OpenAI encourages developers to fine-tune the models for custom applications across industries.

Where can you get gpt-oss?
The models are available for download from HuggingFace and OpenAI’s repositories for local deployment.