Cerebras
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Cerebras CS-3 vs SambaNova DataScale SN40L comparison
Cerebras generates 4,400 tokens per second on the GPT-OSS 120B model using a single CS-4 rack, significantly outperforming SambaNova’s 708 tokens per…
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The Cerebras CS-3 delivers 2,500 tokens per second for Llama 4 Maverick
Cerebras CS-3 delivers Llama 4 Maverick inference at 2,500 tokens per second per user, significantly outperforming the NVIDIA DGX B200. The WSE-3…
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Cerebras undercuts GPU tokens through wafer-scale speed
Cerebras Inference delivers Llama 3.1 70B at 446 tokens per second for $0.6 per 1M tokens, significantly outperforming H100 clusters. The company’s…
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Cerebras CS-3 wafer-scale engine and sparse MoE training explained
The Cerebras WSE-3 integrates 4 trillion transistors and 900,000 AI cores onto a single 300mm silicon wafer. This monolithic design delivers 125…
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The shift toward wafer-scale AI scaling
The Condor Galaxy network reaches 16 exaFLOPs of capacity through the deployment of Condor Galaxy 3, utilizing 64 Cerebras CS-3 systems. These…
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The SRAM cost trap in wafer-scale training
Prioritizing on-chip SRAM for massive parameter counts can cause the Cerebras CS-3 TCO advantage to vanish. Storing a Qwen3-235B model with 131K…
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Cerebras and G42 expand AI supercomputing with Condor Galaxy 3
Cerebras and G42 have launched Condor Galaxy 3, a supercomputing cluster delivering 8 exaFLOPs of AI performance using 64 Cerebras CS-3 systems.…
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Massive capital concentration in AI semiconductor design startups
Nvidia and AMD lead massive capital concentration in AI infrastructure, with top firms like ChangXin Memory Technologies and Cerebras accounting for 42%…
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SambaNova SN50 vs Cerebras WSE-3 for large scale inference
SambaNova SN50 delivers 5x the maximum speed and 3x the throughput for agentic inference compared to Blackwell B200 GPUs. Cerebras WSE-3 provides…