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// Run models locally

DeepInfer

The open-source release of the inference framework behind DeepSeek’s production services (repo created 2026-10-16, ~18k stars in a week): currently DeepSeek-V4.1-Flash only, offering offline inference with the core features for serving at scale — FlashMLA / DeepGEMM / DeepEP kernels, attention DP + MoE EP/EPLB, draft-token decoding (DSpark), async scheduling, batch-invariant and deterministic sampling, structured outputs. Runs on NVIDIA SM100 (Blackwell) and Huawei Ascend 950 only; the KV-cache system, prefill/decode disaggregation and load balancing needed for a full online service are not included

Open source Maintained For developers

IN ONE PARAGRAPH

DeepInfer is the open-source release of the inference framework behind DeepSeek’s production services (repo created 2026-10-16, ~18k stars in a week): currently DeepSeek-V4.1-Flash only, offering offline inference with the core features for serving at scale — FlashMLA / DeepGEMM / DeepEP kernels, attention DP + MoE EP/EPLB, draft-token decoding (DSpark), async scheduling, batch-invariant and deterministic sampling, structured outputs. Runs on NVIDIA SM100 (Blackwell) and Huawei Ascend 950 only; the KV-cache system, prefill/decode disaggregation and load balancing needed for a full online service are not included.

Good for: Developers and teams who want to run models locally.

01How to start

  1. 1Read the official quick-start (link above).
  2. 2Install or sign up as the official guide describes.
  3. 3Try it on a small example before wiring it into a project.

02Alternatives & comparison

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03Related

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