DeepSeek open-sources DeepInfer, its inference framework for serving models at scale

AIDeepSeek says it is open-sourcing DeepInfer, its in-house inference framework that powers DeepSeek-V4.1-Flash at scale. The framework supports Nvidia and Huawei Ascend hardware, along with distributed inference, speculative decoding, SWA Bounded Replay, and structured outputs.

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DeepSeek is open-sourcing DeepInfer, its internal framework for serving models at scale.

Inference frameworks coordinate compute clusters to shape AI throughput, latency, cost, and energy efficiency. DeepSeek says DeepInfer powers high-throughput, low-latency inference for V4.1 Flash.

Supporting both Nvidia and Huawei Ascend hardware, DeepInfer enables distributed inference, speculative decoding, SWA Bounded Replay, and structured outputs. Alongside the framework, DeepSeek also released deepseek-recipe, a production-grade tokenization component fully aligned with its official API.

DeepSeek@deepseek_ai

🚀 Introducing DeepInfer, our in-house inference framework, now fully open source! Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable. 🔗 http://github.com/deepseek-ai/DeepInfer 1/4

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X.PIN · x.comPublished Oct 21, 5:26 AM ET · added here 5:56 AM ET

Original title: DeepSeek is open-sourcing DeepInfer, its internal framework for serving models at scale.

DeepSeek open-sources DeepInfer, its inference framework for serving models at scale

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