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DeepSeek V4.1 Flash: Large-Scale Inference Deployment
DeepSeek's inference stack reportedly processes 155 trillion tokens daily, achieving $38 revenue per GPU-hour through aggressive distributed serving and speculative decoding.
What: The DeepInfer framework integrates distributed inference, caching, and speculative decoding to maximize throughput. It is reportedly used to serve massive traffic volumes while the company open-sources portions of its internal infrastructure.
Why it matters: This demonstrates the massive financial and operational scale of modern inference, where engineering efficiency directly dictates the per-token cost advantage.
Decoder
- Speculative decoding: A technique where a smaller, faster model predicts a sequence of tokens that a larger, slower model validates in parallel, significantly increasing generation speed.
Original article
DeepInfer combines distributed inference, caching, load balancing, and speculative decoding to improve efficiency. DeepSeek processes 155 trillion tokens daily per cluster and earns $38 in revenue per GPU-hour while open-sourcing much of its inference framework.
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