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DeepSeek open-sources DeepInfer, the inference framework behind its production services
See how this story connectsDeepSeek published DeepInfer on GitHub on 20 October 2026 under the Apache 2.0 licence. The README calls it the inference framework behind DeepSeek’s production services and says the release provides offline inference for DeepSeek-V4.1-Flash on NVIDIA SM100 GPUs and Huawei Ascend 950 NPUs, with the company’s own kernels (FlashMLA, DeepGEMM, DeepEP, TileKernels, DeepSelect), draft-token decoding with confidence-scheduled verification, asynchronous batch scheduling, batch-invariant inference, deterministic sampling and structured outputs. A KV cache system, prefill and decode disaggregation and load balancing across replicas are needed for a complete service and are not in the release. The framework was built on vLLM. SCMP reports that a technical article DeepSeek posted on Zhihu the same day puts the revenue from one cluster serving V4.1-Flash on DeepInfer at the equivalent of US$38 per GPU per hour at off-peak prices, and quotes the company saying the release helps the community lower compute costs and energy use.
Why it matters
Providers serving the open-weight V4.1-Flash can run DeepSeek’s own serving code on NVIDIA Blackwell or Huawei Ascend hardware, with the cache and routing layers left for them to build.
- When
- 20 Oct 2026
- ID
WTA-N-2026-0349- Where
- China
- Who
- DeepSeek, NVIDIA, Huawei
- Topics
- Frontier models, Chips, Open-weight models
Summary by wheresthe.ai, from DeepSeek (GitHub) and the reporting credited above. Checked against the source on 21 Oct 2026.
Source copy: download the page text as saved on 21 Oct 2026 (PDF). Also held by the Internet Archive.
Cite this story
WTA-N-2026-0349: “DeepSeek open-sources DeepInfer, the inference framework behind its production services.” wheresthe.ai, 20 Oct 2026. https://wheresthe.ai/d/cn-deepseek-open-sources-deepinfer-inference-framework-2026-10/ (source: DeepSeek (GitHub)).
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