Checked fact 43459 Nov 2026Research

Nvidia's developer blog post of 6 November 2026 reports NeMo RL weight-refit latency for DeepSeek v3 671B on NVIDIA DGX H100 of 14.9 s with gather-and-broadcast and 2.6 s with Reshard (PP16 x EP16 to TP32 x DP8).

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The exact words it rests on

NVIDIA DGX H100 DeepSeek v3 671B PP16 x EP16 → TP32 x DP8 14.9 s 2.6 s

What the source said when we opened it, on 9 Nov 2026.

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Accelerating Reinforcement Learning Weight Refit with the Reshard Collective
NVIDIA · 2026-11-06

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Checked by the notis newsroom on 9 Nov 2026, against the source above.

In the story

Nvidia reports its Reshard call cuts DeepSeek-V3 weight refit from 14.9 to 2.6 seconds in its own tests. 9 Nov 2026

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The company says: “Nvidia's developer blog post of 6 November 2026 reports NeMo RL weight-refit latency for DeepSeek v3 671B on NVIDIA DGX H100 of 14.9 s with gather-and-broadcast and 2.6 s with Reshard (PP16 x EP16 to TP32 x DP8).” ai notis, checked 9 Nov 2026. Source: Accelerating Reinforcement Learning Weight Refit with the Reshard Collective (NVIDIA). https://ainotis.com/c/4345

As a reference (APA style)

ai notis. (2026, November 9). The company says: Nvidia's developer blog post of 6 November 2026 reports NeMo RL weight-refit latency for DeepSeek v3 671B on NVIDIA DGX H100 of 14.9 s with gather-and-broadcast and 2.6 s with Reshard (PP16 x EP16 to TP32 x DP8) [Checked claim 4345]. ai notis. https://ainotis.com/c/4345

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