---
格式版本: 2
标题: "GB300 NVL72 Spectrum-X RoCE - CoreWeave Docs"
原文链接: "https://docs.coreweave.com/platform/instances/gpu/gb300-4x-e"
发布日期: "未标注"
发现时间: "2026-06-01T16:19:30+08:00"
入库时间: "2026-06-01T14:46:59.066Z"
来源平台: "SerpApi Google"
搜索渠道: "serpapi"
搜索词: "NVL72"
匹配关键词:
  - "NVL72"
  - "GPU"
  - "NVIDIA"
  - "Nvlink"
相关厂家:
  - "NVIDIA"
相关专家:
  []
内容类型: "网页"
抓取工具: "XCrawl Scrape"
清洗工具: "XCrawl Markdown + LLM 正文裁剪"
原始附件:
  []
AI优质: "是"
AI打分: 86
AI分档: "高置信优质"
AI质检状态: "通过"
AI打分理由: "核心云厂商官方文档，直接披露NVL72机柜级架构、GB300超节点规格、NVLink 5代与Spectrum-X RoCE互连细节，具备明确商业部署信号与技术参数，信息完整且前沿。"
AI质检模型: "qwen3.6-plus"
AI质检时间: "2026-06-02T23:16:24+08:00"
AI主题相关性: 18
AI来源权威性: 13
AI新颖性: 18
AI技术细节: 16
AI商业部署信号: 12
AI完整性: 9
采集批次: "2026年6月1日16点18分53秒"
采集批次ID: "20260601-161853-741"
去重键: "https://docs.coreweave.com/platform/instances/gpu/gb300-4x-e"
---

# GB300 NVL72 Spectrum-X RoCE

Powered by four NVIDIA GB300 Superchips, each featuring a “Blackwell Ultra” GPU with an unprecedented 279 GB of memory, these instances represent the absolute pinnacle of our high-performance computing offerings. These instances form part of a larger NVL72 rack architecture which boasts 21 TB of total GPU memory, interconnected by 5th-generation NVLink for a seamless, rack-scale memory fabric. For clustering, they are equipped with next-generation NVIDIA Spectrum-X RoCE (RDMA over Converged Ethernet), leveraging BlueField-3 and ConnectX-8 SuperNICs for large scale AI in Ethernet-based cloud environments.

## Specifications

| Feature | Detail |
|---|---|
| **Category** | State-of-the-Art Compute |
| **Instance ID** | `gb300-4x-e` |
| **GPU** | 4x NVIDIA GB300 |
| **GPU RAM** | 279 GB |
| **GPU Connectivity** | Spectrum-X RoCE & NVLink |
| **CPU Model** | 2x NVIDIA Grace Arm v9 (3.10 GHz) |
| **vCPUs** | 144 |
| **RAM** | 960 GB |
| **Local Storage** | 61.44 TB |
| **Network Speed** | Dual-port 200GbE |
| **Availability** | Contact sales for availability |

## Primary use cases

Training next-generation foundation models in the trillion-parameter class, massive-scale and high-fidelity inference on the most complex AI models, and scientific simulations requiring maximum memory capacity and the fastest data throughput.

Next-generation frontier models (multi-trillion parameters), state-of-the-art multimodal systems, and large-scale scientific discovery models.