SAN FRANCISCO, Aug 27 (Reuters) - Cerebras Systems

launched on Tuesday a tool for AI developers that allows them to

access the startup's outsized chips to run applications,

offering what it says is a much cheaper option than

industry-standard Nvidia ( NVDA ) processors.

Access to Nvidia ( NVDA ) graphics processing units (GPUs) - often

via a cloud computing provider - to train and deploy large

artificial intelligence models used for applications such as

OpenAI's ChatGPT can be difficult to obtain and expensive to

run, a process developers refer to as inference.

"We're delivering performance that cannot be achieved by a

GPU," Cerebras CEO Andrew Feldman told Reuters in an interview.

"We're doing it at the highest accuracy, and we're offering it

at the lowest price."

The inference portion of the AI market is expected to be

fast-growing and attractive - ultimately worth tens of billions

of dollars if consumers and businesses adopt AI tools.

The Sunnyvale, California-based company plans to offer

several types of the inference product via a developer key and

its cloud. The company will also sell its AI systems to

customers who prefer to operate their own data centers.

Cerebras' chips - each the size of a dinner plate and called

Wafer Scale Engines - avoid one of the issues with AI data

crunching: the data crunched by large models that power AI

applications typically won't fit on a single chip and can

require hundreds or thousands of chips strung together.

That means Cerebras' chips can achieve speedier

performances, Feldman said.

It plans to charge users as little as 10 cents per million

tokens, which are one of the ways companies can measure the

amount of output data from a large model.

Cerebras is aiming to go public and filed a confidential

prospectus with the Securities and Exchange Commission this

month, the company said.