ChatGPT offline: guide to having free AI without internet on your PC

What happened?

In June 2025, OpenAI launched GPT-OSS, a series of open-source models based on GPT-4. This move represents a significant strategic shift for a company that had previously kept its most advanced models under strict commercial licenses. Unlike chatbots like ChatGPT, Claude, or Gemini, these models are downloaded and run locally on any PC or Mac with at least 16 GB of RAM, without needing an internet connection. Tools like LM Studio make installation easy, allowing users with modest hardware to have a functional and free AI assistant. According to Hipertextual, the models are available in multiple sizes, from lightweight 7 GB versions to larger configurations requiring up to 32 GB of RAM. This release is not isolated: it responds to a growing trend of AI democratization, where projects like Meta's Llama and Mistral had already paved the way. However, OpenAI's decision to open part of its technology marks a milestone, as the company had been criticized for its closed and costly approach.

Why is it important?

This move democratizes access to high-level artificial intelligence. Until now, assistants like ChatGPT, Claude, or Gemini required a permanent connection and had increasingly restrictive usage limits. With GPT-OSS, anyone can run a model capable of programming, creative writing, and image analysis without relying on external servers, ensuring total privacy and zero recurring costs. The historical context is key: since the launch of ChatGPT in 2022, generative AI has been dominated by large corporations that control access and data. GPT-OSS breaks that paradigm, similar to what happened with Linux versus proprietary operating systems. For users in regions with limited connectivity or those concerned about privacy, this option removes barriers. Additionally, running locally avoids the risks of sending sensitive data to the cloud, a critical point for sectors like healthcare or finance. According to experts cited by Hipertextual, GPT-OSS performance is comparable to GPT-4 in common tasks, though inferior to GPT-4o or GPT-5 in advanced benchmarks.

What consequences will it have?

For businesses, local execution reduces security risks by not sending sensitive data to the cloud. For users, it eliminates the need for subscriptions and allows use in areas without connectivity. However, the models are not as powerful as GPT-4o or GPT-5, and require basic technical knowledge for installation. In the long term, it could pressure other companies to release open versions of their models. This phenomenon was already observed when Meta launched Llama 2 in 2023, forcing others to follow suit. The market impact is twofold: on one hand, companies like Google and Anthropic may feel pressure to offer local alternatives; on the other, startups specializing in local AI, like LM Studio or Ollama, benefit directly. However, challenges exist: installation requires at least 16 GB of RAM, and without a dedicated GPU, performance can be slow. Additionally, the models inherit biases from GPT-4, which could raise ethical issues. Despite this, the decentralization of AI is a step toward a more equitable ecosystem, where control does not rest solely with a few corporations.

What should readers know?

• GPT-OSS models are based on GPT-4, not the latest versions like GPT-4o or GPT-5.
• At least 16 GB of RAM is required; the smallest variant takes about 7 GB of disk space, while larger ones require up to 32 GB.
• LM Studio is the simplest tool to download and run the models, but alternatives like Ollama or GPT4All also exist.
• Performance depends on hardware: dedicated graphics cards (NVIDIA, AMD) significantly speed up the process.
• There are no usage limits or additional censorship, but the model may have inherited biases from GPT-4, such as gender or racial biases.
• Privacy is total: data never leaves the device, ideal for sensitive information.
• OpenAI has released the models under a permissive license, allowing commercial use and modification.

"GPT-OSS represents an important step toward decentralized AI, where control of data and access does not depend on large corporations."

Compared to the launch of Llama 2, GPT-OSS offers superior performance in reasoning and creativity tasks, but with higher hardware requirements. While Llama 2 could run on devices with 8 GB of RAM, GPT-OSS requires double that. This limits adoption on older hardware but makes it accessible to most modern computers. Looking ahead, OpenAI is expected to release optimized versions for mobile devices, following the trend of models like Google's Gemma. For developers, GPT-OSS opens the door to offline AI applications, such as offline assistants for customer service or educational tools in rural areas. The local AI market, valued in the billions, could grow exponentially with this offering. However, the project's sustainability will depend on community support and periodic updates from OpenAI.