---
格式版本: 2
标题: "NVIDIA AI Factory Compute Is Becoming an Investable Asset Class"
原文链接: "https://blogs.nvidia.com/blog/nvidia-ai-factory-compute/"
发布日期: "2026-08-11"
发布时间校准状态: "found"
发布时间需复核: "否"
发布时间来源: "llm:scrape:strict_html_body"
发布时间证据: "div class=author_meta text-xs text-nvidia-text-tertiary mb-[15px]: August 11, 2026 by Jensen Huang"
发布时间校准原因: "标题附近作者元数据明确标注 publication date 为 August 11, 2026，优先级高于 article:published_time 元数据。"
发布时间校准置信度: "1"
发布时间候选数量: 12
发布时间严格候选数量: 3
发布时间原页读取状态: "source template page reused from URL open"
发布时间未找到原因: ""
发布时间校准时间: "2026-08-12T17:50:35+08:00"
发布时间仲裁状态: "confirmed"
发布时间仲裁尝试次数: 1
发布时间仲裁耗时毫秒: 4529
发现时间: "2026-08-12T17:49:45+08:00"
入库时间: "2026-08-12T09:50:40.071Z"
来源平台: "NVIDIA Blog 搜索"
搜索渠道: "source_template"
搜索词: "https://blogs.nvidia.com/?s=AI%20Rack"
匹配关键词:
  - "AI Rack"
  - "AI"
  - "GPU"
  - "performance"
相关厂家:
  - "NVIDIA"
相关专家:
  []
内容类型: "网页"
抓取工具: "Free Fetch + Defuddle"
清洗工具: "Defuddle Markdown + Defuddle/Readability 正文提取"
原始附件:
  []
AI优质: "否"
AI打分: 56
AI分档: "召回候选"
AI质检状态: "不通过"
AI打分理由: "文章主要讨论NVIDIA与金融机构合作融资建设AI基础设施，属于宏观金融模式，未涉及超节点/AI Rack具体架构、技术细节或量产落地信息，技术细节极低，商业信号为合作融资但无具体部署客户。"
AI质检模型: "ali-deepseek-v4-flash"
AI质检时间: "2026-08-12T17:50:48+08:00"
AI主题相关性: 12
AI来源权威性: 15
AI新颖性: 10
AI技术细节: 2
AI商业部署信号: 9
AI完整性: 8
采集批次: "2026年8月12日17点49分42秒"
采集批次ID: "20260812-174942-139"
去重键: "https://blogs.nvidia.com/blog/nvidia-ai-factory-compute"
---

We [announced partnerships](https://nvidianews.nvidia.com/news/nvidia-partners-with-apollo-blackrock-blackstone-brookfield-goldman-sachs-and-kkr-to-establish-ai-compute-infrastructure-financing-platforms-to-mobilize-over-500-billion-of-third-party-capital) with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent financing platforms designed to mobilize over $500 billion of third-party capital to support the buildout of AI infrastructure over time.

This is a major milestone for NVIDIA and the AI industry. We have moved from an era in which companies bought chips and built data centers project by project to one in which AI factories can be financed as productive infrastructure — with repeatable platforms, long-term institutional capital and a diverse customer base that uses compute to create revenue.

AI has reached an inflection point. It is moving from research into production. AI is creating real value, and the infrastructure behind it is becoming one of the world’s most productive assets. In AI, compute is revenue.

## A New Infrastructure Asset

NVIDIA compute is not just a chip. It is a complete AI factory platform including accelerated computing, networking, systems software, AI frameworks and a global developer ecosystem.

NVIDIA DSX AI factories can run the world’s broadest range of AI models, modalities and algorithms — language, vision, speech, biology, physical AI and robotics. One NVIDIA AI factory can serve many customers and many workloads. That makes it flexible and fungible.

It is also built on a globally adopted architecture used across every major cloud, and by systems makers and enterprises around the world. When needs change, the factory can be used by another customer, another cloud or another operator. This broad ecosystem gives NVIDIA compute a deep market of potential users and offtakers, helping protect residual value.

CUDA makes the factory better over time. Every generation of NVIDIA software improves the performance, efficiency and total cost of ownership of already- installed infrastructure. The hardware does not stand still: software innovation allows an AI factory to produce more intelligence at lower cost throughout its life, extending its useful economic value.

NVIDIA A100 is a powerful example. NVIDIA introduced the Ampere-based A100 in 2020, and six years later, it remains in active commercial use for AI training, fine-tuning, inference and high-performance computing. Customers continue to commit capacity for multi-year deployments, extending A100’s economic life toward a decade.

The market is also demonstrating the durability of NVIDIA compute economics. One-year H100 rental pricing rose from about $1.70 per GPU-hour in October 2025 to about $2.35 per GPU-hour in March 2026. Cross-provider on-demand median pricing rose from roughly $2.00 per GPU-hour in October 2025 to $2.70 in June 2026. Blackwell capacity commands a premium, with reported B200 cloud rates spanning approximately $5.30 to $7.05 per GPU-hour.

That is what makes NVIDIA AI factories different. Their value is not fixed at installation: CUDA continuously improves their output; the installed base remains productive well beyond its initial depreciation period; and the same standard architecture serves a deep, growing global market of AI workloads.

These are the characteristics of an investable infrastructure asset: it produces revenue, serves a broad market, improves in performance over time and can be redeployed.

## Bringing Capital to AI Factories

The demand for AI infrastructure is extraordinary. But access to capital is uneven. Many great AI companies, enterprises and AI clouds have demand for compute but do not yet have access to financing at the scale or cost required to build quickly.

That is why we are partnering with the world’s leading long-term capital providers.

Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR are also among the world’s leading infrastructure investors, with deep expertise in underwriting long-lived, productive assets. Together, we are creating repeatable financing platforms to help the AI ecosystem build the factories it needs.

The platforms are designed to help qualified AI labs, enterprises and AI clouds access AI-factory infrastructure at scale. The more than $500 billion figure represents aggregate third-party capital that these platforms are designed to mobilize over time — the capital is not NVIDIA revenue, a single fund or a commitment to a single customer.

The financial institutions will independently assess each opportunity — the customer, demand, utilization, cash flow and residual value. NVIDIA provides the AI factory platform. The financial institutions provide long-term capital and financing expertise.

## The Important Questions

### Is this circular financing?

This initiative is designed to address that concern. We are bringing independent, long-term institutional capital into the AI infrastructure market.

The demand is real: it comes from frontier AI labs, AI-native startups, enterprises, cloud providers and countries building AI services. The capital providers independently underwrite each project — including the customer, demand, utilization, cash flow and residual value. NVIDIA provides the platform; the investors make independent financing decisions.

This is the beginning of an open capital market for AI infrastructure.

### Why would NVIDIA support financing?

In some cases, NVIDIA may provide a residual-value support mechanism for up to 25% of an opportunity, assessed carefully on a project-by-project basis. That support is limited, residual-value based and designed to complement — not replace — independent underwriting.

This is substantially lower than other compute-financing arrangements. NVIDIA can provide support because NVIDIA compute is unique: it is fungible, universally adopted, software-upgradable and redeployable across a large ecosystem of customers.

Our role is to help unlock a very large pool of independent capital while maintaining disciplined risk exposure.

### Can the market absorb this capacity?

The question is not whether we are building data centers. The question is whether we are building productive AI factories.

An AI factory turns energy and data into valuable intelligence. Its customers are broad: frontier AI labs, AI clouds, enterprises and nations. They are building AI because it has become useful — doing valuable work across every industry.

There is discipline in the model. Each financing partner will independently evaluate demand, utilization, cash flow and residual value. Capacity will be built around real customer economics.

### Where is the return on investment?

The return is in the usefulness of AI.

Companies are using AI to write software, discover drugs, design products, serve customers, automate operations and build new services. AI factories make this possible. More compute creates better AI; better AI creates more usage; more usage creates more revenue; and more revenue drives more compute.

This is the virtuous cycle of the AI industrial revolution.

## The Infrastructure of Intelligence

Every industrial revolution has been built on infrastructure: electricity, transportation, communications and computing, with every buildout enabled by external financing.

AI factories are the infrastructure of the intelligence era.

With these partnerships, NVIDIA and the world’s leading financial institutions are creating a new way to finance the infrastructure that will power this industrial revolution. We will make AI factories more accessible to the companies, industries and nations building the future.

The age of AI is here. Together, we will build the infrastructure to power it.
