DeepSeek open-sources the DeepInfer inference framework, processing 155 trillion tokens per day on a single cluster
DeepSeek has open-sourced DeepInfer, the production inference framework supporting V4.1 Flash, and published production data including 155 trillion tokens processed per day on a single cluster, a 96% input cache hit rate, an average 400ms time to first token, and 230 tokens/s generation. The framework is customized based on vLLM and uses the Apache 2.0 license, supports distributed inference, speculative decoding, SWA Bounded Replay and structured output, and targets NVIDIA SM100 and Huawei Ascend 950. DeepSeek says components such as KV cache management and load balancing are not fully open-sourced because they are coupled with internal infrastructure, while the vLLM team reports that under matched GB200 configurations, decoding throughput differs from DeepInfer's published results by less than 6%.
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The original article breaks down DeepInfer's architecture, cache tiering and cost estimates, and includes vLLM comparison reproduction results, making it easier to judge the transferable boundaries of this inference stack.
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