IX2-0144
① SA Source
- Source: 開啟完整 SA 文章
- Section:
Nvidia TensorRT LLM and NVL72 - Line hint:
232
Context Before
Source: SemiAnalysis InferenceX ↗
Nvidia TensorRT LLM and NVL72
Evidence
TensorRT LLM already serves billions of tokens per hour globally across providers like TogetherAI and other advanced providers, and it has really allowed the GB200 NVL72 and GB300 NVL72 to shine, delivering more than double the performance at high throughput
Context After
② Atomic Claim
TensorRT LLM 已充分發揮 GB200 NVL72 與 GB300 NVL72 的能力，在高 throughput 區間提供超過兩倍效能。
- Epistemic Mode:
ASSERTED - Mapping Status:
COMPLETE
③ Semantic Frame
{
"comparison_expression": "TensorRT LLM 已充分發揮 GB200 NVL72 與 GB300 NVL72 的能力，在高 throughput 區間提供超過兩倍效能。",
"entities": [
{
"id": "04_knowledge_base/Large language model",
"label": "LLM"
},
{
"id": "04_knowledge_base/GB200 NVL72",
"label": "GB200 NVL72"
},
{
"id": "04_knowledge_base/GB300 NVL72",
"label": "GB300 NVL72"
}
],
"frame_type": "COMPARISON",
"metric": "THROUGHPUT",
"operator": "MULTIPLE_OF",
"qualifiers": {
"condition_text": null,
"numeric_mentions": [],
"temporal_mentions": []
}
}④ Canonical Entity Mapping
| Role | Surface Label | Canonical Target |
|---|---|---|
| comparison_entity_0 | LLM | 04_knowledge_base/Large language model |
| comparison_entity_1 | GB200 NVL72 | 04_knowledge_base/GB200 NVL72 |
| comparison_entity_2 | GB300 NVL72 | 04_knowledge_base/GB300 NVL72 |
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。