Perplexity
@perplexity_ai
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We published new research on how we serve post-trained Qwen3 235B models on NVIDIA GB200 NVL72 Blackwell racks.
GB200 is a major step up over Hopper for high-throughput inference on large MoE models, not just a training platform.
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We’ve developed our own inference engine Runtime-Optimized Serving Engine (ROSE) to serve models ranging from embeddings to trillion-parameter LLMs.
With CuTeDSL integrated into our inference engine, Perplexity can build the specialized GPU kernels faster to bring models up to peak performance on NVIDIA Hopper and Blackwell GPUs.
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Announcing Personal Computer.
Personal Computer is an always on, local merge with Perplexity Computer that works for you 24/7.
It's personal, secure, and works across your files, apps, and sessions through a continuously running Mac mini.
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