By Anna Tong
SAN FRANCISCO (Reuters) -OpenAI said on Tuesday it has released two open-weight language models that excel in advanced reasoning and are optimized to run on laptops with performance levels similar to its smaller proprietary reasoning models.
An open-weight language model’s trained parameters or weights are publicly accessible, which can be used by developers to analyze and fine-tune the model for specific tasks without requiring original training data.
“One of the things that is unique about open models is that people can run them locally. People can run them behind their own firewall, on their own infrastructure,” OpenAI co-founder Greg Brockman said in a press briefing.
Open-weight language models are different from open-source models, which provide access to the complete source code, training data and methodologies.
The landscape of open-weight and open-source AI models has been highly contested this year. For a time, Meta’s Llama models were considered the best, but that changed earlier this year when China’s DeepSeek released a powerful and cost-effective reasoning model, while Meta struggled to deliver Llama 4.
The two new OpenAI models are the first open models OpenAI has released since GPT-2, which was released in 2019.
OpenAI’s larger model, gpt-oss-120b, can run on a single GPU, and the second, gpt-oss-20b, is small enough to run directly on a personal computer, the company said.
OpenAI said the models have similar performance to its proprietary reasoning models called o3-mini and o4-mini, and especially excel at coding, competition math and health-related queries.
The models were trained on a text-only dataset which in addition to general knowledge, focused on science, math and coding knowledge. OpenAI did not release benchmarks comparing the open-weight models to competitors’ models such as the DeepSeek-R1 model.
Microsoft-backed OpenAI, currently valued at $300 billion, is currently raising up to $40 billion in a new funding round led by Softbank Group.
(Reporting by Anna Tong in San Francisco; Editing by Edwina Gibbs)
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