VR2R-0092_r1

VR2R-0092

① SA Source

• Source: 開啟完整 SA 文章
• Section: Rubin
• Line hint: 79

Context Before

This means the sparser the workload, the closer the performance will be to the 50 PFLOPS marketed peak performance.

Evidence

NVIDIA thus brands the 50 PFLOPS figure as FP4 Inference while the 35 PFLOPS FP4 Training number is for dense workloads.

Context After

As accuracy is preserved, this allows the marketing team to claim 5x FLOPs for Rubin over GB200, comparing 50 PFLOPS dynamically compressed FP4 to 10 PFLOPS dense FP4. Whether actual GEMM performance reaches 50 PFLOPS depends on how many zeros are in the tensor.

② Atomic Claim

因此 NVIDIA 將 50 PFLOPS 數字標示為 FP4 Inference，而 35 PFLOPS 的 FP4 Training 數字則對應 dense workloads。

• Epistemic Mode: INFERRED
• Mapping Status: COMPLETE

③ Semantic Frame

{
  "attribute": "FP4_PERFORMANCE_MARKETING_LABELS",
  "context_nodes": [
    {
      "id": "04_knowledge_base/FP4",
      "label": "FP4"
    }
  ],
  "entity": {
    "id": "02_companies/NVDA",
    "label": "NVIDIA"
  },
  "frame_type": "ATTRIBUTE",
  "qualifiers": {
    "condition_text": null,
    "numeric_mentions": [
      "50 PFLOPS",
      "35 PFLOPS"
    ],
    "temporal_mentions": []
  },
  "value": {
    "numeric_mentions": [
      "50 PFLOPS",
      "35 PFLOPS"
    ],
    "value_text": "50 PFLOPS 標示為 FP4 Inference；35 PFLOPS FP4 Training 對應 dense workloads。"
  }
}

④ Canonical Entity Mapping

Role	Surface Label	Canonical Target
entity	NVIDIA	NVDA
context_node	FP4	FP4

⑤ Human Review

請在 Properties 逐項確認：

• 原文 → Atomic Claim 是否忠實
• Atomic Claim → Semantic Frame 是否忠實
• Canonical Entity mapping 是否正確
• Epistemic mode 是否保留原文語氣
• 最後選擇 review_action

Review state

Markdown 內文不是正式 approval。只有 Apply bridge 寫入的 Decision Ledger event 才是正式決策。