Cerebras, the AI infrastructure firm, announced on July 8 that it will deploy Alibaba’s flagship Qwen3 reasoning model, featuring 235 billion parameters, on Cerebras hardware. The model is claimed to run at 1,500 tokens per second.

“That means reasoning time goes from 60 seconds on GPUs to just 0.6 seconds,” said the company in the announcement. Cerebras added that it is enabling the model with 131k context for enterprise customers, which allows production-grade code generation. 

The model will be available for all to try later this week at Cerebras. 

The company develops wafer-scale AI chips optimised for inference — a process which involves deriving insights from pre-trained AI models. Its cloud services host a range of AI models powered by its hardware, allowing users and developers to generate over 1,000 tokens per second. 

In AI models, ‘reasoning’ involves using extra computation to analyse a user query step-by-step, aiming for an accurate and relevant answer. This process can be time-consuming, sometimes taking several minutes to complete. 

Custom hardware systems often surpass the inference performance of traditional NVIDIA GPUs, which are frequently used for training and deploying AI models. 

Along with Cerebras, companies like Groq and SambaNova have built hardware that offers superior performance for inference. 

In May, Cerebras announced that its hardware has outperformed NVIDIA’s DGX B200, which consists of 8 Blackwell GPUs, in terms of output speed while deploying Meta’s Llama 4 Maverick model. 

Cerebras achieved an output token speed of over 2,500 tokens per second, whereas NVIDIA demonstrated an output token speed of only 1,000 tokens per second. 

However, NVIDIA outperformed systems from Groq, AMD, Google, and other vendors. “Only Cerebras stands – and we smoked Blackwell,” said Cerebras in a post on X. “We’ve tested dozens of vendors, and Cerebras is the only inference solution that outperforms Blackwell for Meta’s flagship model,” said the company. 

OpenAI is doubling down on its commitment to democratise AI education by launching large-scale initiatives in the United States. The company has partnered with the American Federation of Teachers (AFT) to launch the National Academy for AI Instruction, a five-year initiative aimed at training four lakh K-12 teachers, nearly one in 10 across the country, to use and teach AI in classrooms effectively.

With a $10 million contribution over five years, including $8 million in funding and $2 million in engineering and computing support, OpenAI will help establish a flagship training hub in New York City and support the development of additional centres by 2030.

The initiative promises free workshops, hands-on training, and AI tools specifically built for educators, with a strong focus on equity and accessibility in underserved school districts.

“Educators make the difference, and they should lead this next shift with AI,” OpenAI CEO Sam Altman said, recalling how a high school teacher sparked his own early curiosity in AI.

The academy is also backed by the United Federation of Teachers, Microsoft and Anthropic, and aims to ensure that teachers are at the forefront of setting commonsense guardrails and using AI to enhance, rather than replace, human teaching.

Meanwhile, in a parallel development, OpenAI announced the launch of OpenAI Academy India in collaboration with the IndiaAI Mission under the IT and electronics ministry. This marks the first international expansion of OpenAI’s educational platform, aiming to train one million teachers in generative AI skills.

The partnership will deliver AI training in English and Hindi (with more regional languages to follow), and extend to civil servants via the iGOT Karmayogi platform. Additional efforts include six-city workshops, hackathons across seven states, and $100,000 in API credits to 50 AI startups.

Union minister Ashwini Vaishnaw hailed the initiative as a step towards making AI knowledge accessible to every citizen. Jason Kwon, chief strategy officer at OpenAI, called India “one of the most dynamic countries for AI development”.

OpenAI has hired four senior engineers from xAI, Tesla, and Meta, as reported by WIRED on July 8, citing a Slack message sent by OpenAI’s co-founder, Greg Brockman.

The company has hired David Lau, former VP of software engineering at Tesla; Uday Ruddaraji, the former head of infrastructure engineering at xAI and X; Mike Dalton, an infrastructure engineer from xAI; and Angela Fan, an AI researcher from Meta.

Ruddarraju and Dalton worked on building xAI’s Colossus, the supercomputer comprising more than 200,000 GPUs. 

Soon, Brockman confirmed the same in a post on X.