SAN FRANCISCO, Aug 5 (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.