DeepSeek V4.1 Flash Joins China's Supercomputing Grid: what are the key facts?

The DeepSeek V4.1 Flash model has officially integrated with the National Supercomputing Internet platform.

DeepSeek V4.1 Flash Joins China's Supercomputing Grid: what are the key facts?

This model features a 552B-parameter MoE architecture utilizing an asymmetric Causal structure.

DeepSeek V4.1 Flash Joins China's Supercomputing Grid: what are the key facts?

Compared to its predecessor, HBM requirements dropped to one-quarter and SSD needs fell to one-eighth.

DeepSeek V4.1 Flash Joins China's Supercomputing Grid: what are the key facts?

After post-training via large-scale reinforcement learning, it outperforms flagship models like V4 Pro in benchmarks.

Physix Frontier · News Briefing Card (enbrief · Sep 11, 2026)

DeepSeek V4.1 Flash Joins China's Supercomputing Grid

KEY FACTS

The DeepSeek V4.1 Flash model has officially integrated with the National Supercomputing Internet platform.
This model features a 552B-parameter MoE architecture utilizing an asymmetric Causal structure.
Compared to its predecessor, HBM requirements dropped to one-quarter and SSD needs fell to one-eighth.
After post-training via large-scale reinforcement learning, it outperforms flagship models like V4 Pro in benchmarks.

KEY DATA

552BTotal Parameters

8BInput Activation

16BOutput Activation

To 1/4HBM Requirement Reduction

PHYSIX OBSERVATION

This move marks a critical breakthrough for domestic LLMs in infrastructure adaptation and inference cost optimization. By aggressively compressing KV Cache, it drastically lowers VRAM thresholds for Agent scenarios, making high-performance models easier to deploy at scale. This is not just a technical iteration but signals that AI applications are shifting from 'compute wars' to 'efficiency battles,' benefiting small developers and edge intelligence deployment.

Source: enbrief original report ↗