Compute EvidenceChips · AI · Policy
DatasetGitHub

The research record

The source record.

Inspect the source behind each claim, its strongest qualification, and the questions still open.

21records across 5 cases

4 of 21 evidence records · Pangu domestic training

  1. EV-06supportsModerate confidence

    Huawei reports a 718B-parameter MoE run on 6,000 Ascend 910B NPUs and says its system supports all training stages.

    HuaweiPangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs (opens in new tab)
    Primary sourceTechnical preprintPublished 07 May 2025
    Source details

    Quotation or reported data

    “MFU of 30.0%” on 6,000 Ascend NPUs.
    Exact location
    Paper abstract; sections 1 and 2.2
    Source accessed
    03 Sept 2026

    Counterevidence

    The run is vendor-reported and has no independent full-training audit or reproduction.

    Remaining uncertainty

    Run duration, energy, capital cost, fleet availability, and yield are not disclosed.

  2. EV-07qualifiesHigh confidence

    The model and execution plan were reshaped around NPU constraints, with cumulative interventions raising reported model FLOPs utilization (MFU) by 58.7 percent relative to the baseline.

    HuaweiPangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs (opens in new tab)
    Primary sourceTechnical preprintPublished 07 May 2025
    Source details

    Quotation or reported data

    Table 5 reports a 58.7% relative MFU improvement, reaching 30.0% MFU on 6,000 NPUs; techniques include hierarchical all-to-all, recomputation, and host swapping.
    Exact location
    Section 4.5, Table 5
    Source accessed
    22 Sept 2026

    Counterevidence

    Thirty percent MFU still implies substantial unused peak compute, and no comparable counterfactual run is public.

    Remaining uncertainty

    The incremental burden caused specifically by controls cannot be separated from normal large-model engineering.

  3. EV-08supportsHigh confidence

    The official model card says Pangu Ultra was trained from scratch; the repository publishes roughly 1.47 TB of weights and documents a minimum 32-card Ascend serving setup.

    Huawei openPanguopenPangu Ultra MoE 718B Model (opens in new tab)
    Primary sourceCompany repositoryPublished date unverified
    Source details

    Quotation or reported data

    62 weight shards; four Atlas 800T A2 nodes; 32 64GB cards.
    Exact location
    Model card overview and sections 1, 4.1, and 4.4; file tree
    Source accessed
    03 Sept 2026

    Counterevidence

    Serving reproducibility does not reproduce pretraining or validate the disclosed training fleet.

    Remaining uncertainty

    The complete training corpus, code, and run configuration are not public.

  4. EV-09qualifiesModerate confidence

    BIS assessed that listed Ascend 910-series chips likely involved U.S. design technology, software, or equipment subject to export rules.

    U.S. Bureau of Industry and SecurityGuidance on Application of General Prohibition 10 (GP10) to People’s Republic of China (PRC) Advanced-Computing Integrated Circuits (ICs) (opens in new tab)
    Primary sourceGovernment guidancePublished 13 May 2025
    Source details

    Quotation or reported data

    The illustrative list names Ascend 910B and 910C.
    Exact location
    Pages 1–2, summary, illustrative list, and applicable regulations
    Source accessed
    03 Sept 2026

    Counterevidence

    This is an enforcement assessment, not a bill-of-materials audit of the Pangu fleet or CloudMatrix installation.

    Remaining uncertainty

    The precise origin and legal status of each chip and upstream component are not public.

“Primary” identifies an original or official source for the recorded claim. It does not mean that the finding has been independently verified. Full JSON and CSV datasets are available below.