cerebras

The 5.6 Sol model is coming to Cerebras hardware in July, offering inference at 750 tokens per second.

Cerebras Systems stock dropped nearly 20% after forecasting narrower gross margins despite better-than-expected Q1 earnings; CEO Andrew Feldman said the margin outlook was misunderstood due to equipment rental costs.

A summary of the LatePost interview, reviewing Baidu US R&D's early AI布局, including investing in Cerebras, nearly investing in OpenAI and Anthropic, and the flow of talent from Baidu to these companies.

A model labeled 'GPT 5.5' has appeared on Cerebras via OpenRouter statistics, suggesting a potential secret release or testing phase of a new GPT iteration.

In a tweet, Sarah Hooker argues that GPUs are ill-suited for the long-tail distribution of real-world data, suggesting a need for alternative AI hardware.

The article recounts Baidu Research US's investment in Cerebras, a wafer-scale chip company, a decade ago. It analyzes the shift in the AI chip market from training to inference and the importance of non-consensus investments.

Cerebras stock dropped over 31% within 17 days of its IPO at $311, with criticism about chip limitations and misleading claims.

The article argues that Cerebras chips are optimized for LLM inference and training, not general AI workloads, and cautions against overhyping their ability to challenge NVIDIA across all AI domains.

Cerebras co-founder explains the fundamental difference between WSE (Wafer Scale Engine) and NVIDIA GPU: GPU is designed for graphics, runs AI by stacking cores and NVLink interconnect, while WSE makes the entire wafer into a single chip, with on-chip interconnect bandwidth and memory bandwidth far exceeding GPU clusters, greatly leading in inference speed.

AI infrastructure startups Modal, Cerebras, Exa, and TurboPuffer have shown outstanding performance in the past week.

The co-founder of Cerebras explains how their Wafer-Scale Engine (WSE) simplifies design compared to traditional NVIDIA GPUs.

Cerebras is now running Kimi K2.6, a trillion-parameter model, in enterprise trials at ~1,000 tokens/s, the fastest frontier model performance ever measured by Artificial Analysis.

Cerebras announces that it is now running Kimi K2.6, an AI model from Moonshot AI, on its hardware.

Cerebras announces it is running Kimi K2.6, a trillion parameter model, at approximately 1,000 tokens per second in enterprise trials, claiming the fastest frontier model performance ever measured by Artificial Analysis.

Cerebras CFO announces that the company is internally running GPT5.4 and GPT5.5 on its chips and will release the models to the public soon, promising high-speed AI inference.

Daria Soboleva reflects on her five-year journey with AI hardware company Cerebras, which recently went public, sharing gratitude for colleagues and excitement for the future.

Cerebras Systems raised $5.5B in its IPO, with shares surging 108% on the first day, valuing the company at $66 billion. The AI chip maker, a competitor to Nvidia, overcame regulatory hurdles and reported strong financials.

Cerebras, an AI chipmaker, raised $5.5 billion in its US IPO, becoming the year's largest IPO with a market valuation of about $40 billion.

This article analyzes Cerebras' upcoming IPO as a signal of the 'inference shift' in AI hardware, arguing that while Nvidia dominates GPU-based training, the future of AI compute is becoming increasingly heterogeneous to support inference workloads.

Cerebras Systems is raising its initial public offering price range to $150-$160 amid reports of surging investor demand.