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YouTube · Evolving AI
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The Cerebras WSE-3 Turbo packs 4 trillion transistors, 900,000 AI-optimized cores and 44GB of on-chip SRAM, while delivering up to 250 PFLOPS of AI compute and 43.2 PB/s of memory bandwidth per wafer. The CS-4 combines three WSE-3 Turbo processors in one rack for 750 PFLOPS of AI performance and 129.6 PB/s of aggregate memory bandwidth. In this video, we break down Cerebras CS-4 vs GPU-based AI systems, its claimed 4,400+ tokens per second on GPT-OSS-120B, ultra-low-latency AI inference, Direct Wafer Links, the new Nexus architecture, and the Wafer Scale Backpack. We also explore why Cerebras believes faster inference could transform AI agents, large language models, and next-generation AI data centers.
As NVIDIA, AMD, AWS, and Cerebras compete to power increasingly massive AI models, wafer-scale computing could become one of the most interesting alternatives to conventional AI GPUs.
#Cerebras #CS4 #AIChips #NVIDIA #ArtificialIntelligence #AIHardware #DataCenter
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