Nvidia has begun pitching its new Vera central processing unit to Chinese clients, with orders potentially opening as early as August to revive stalled hardware sales. The move addresses a critical revenue gap after U.S. export controls and domestic policies severely restricted the company's business, a situation CEO Jensen Huang highlighted in October when he said Nvidia's market share in China had "effectively fallen to zero."
The pitch and pricing
Nvidia is positioning the Vera chip as a solution for agentic AI systems that perform tasks autonomously. The company claims the processor runs up to 1.8 times faster than comparable rival products and is now in full production.
Pricing reflects its enterprise positioning. A single Vera processor will cost "well north" of $20,000 before bulk discounts, according to SemiAnalysis. A fully configured rack of 256 chips runs around $10 million, depending on the memory configuration. Nvidia expects $20 billion in revenue from Vera chip sales by the end of this fiscal year in January.
Early client interest and hurdles
Early signals show some traction among Chinese buyers. One major Chinese cloud company plans to order more than 300 servers, each containing two Vera CPUs, for initial testing.
However, large-scale adoption faces friction - specifically regarding software ecosystem compatibility and the challenge of migrating workloads built around domestic AI chips. To manage these hurdles, Chinese clients plan to deploy the Vera chips initially in their overseas data centers for testing.
Selling CPUs in China also presents fewer regulatory hurdles than selling graphics processing units. While Washington licensed about 10 Chinese firms to buy Nvidia's H200 GPU, Chinese officials have withheld approval, resulting in zero deliveries.
The broader CPU market squeeze
This sales push coincides with a global shift in AI computing from model training to inference, where CPUs face less competition from custom chips. The shift has created a supply shortage.
Intel recently notified Chinese customers of server CPU delivery lead times of up to six months. AMD also flagged that the global CPU market remains tight, with demand outpacing forecasts.
Professionals managing high-value B2B technology pipelines can benefit from targeted training on these specific market dynamics, much like the frameworks provided in the AI Learning Path for Technical Sales Representatives. Optimizing outreach and pipeline management for AI for Sales will be essential as competitors race to capture this constrained market.
Why this matters for sales professionals
The Vera rollout highlights a shift in how enterprise AI hardware is sold. Buyers are no longer just purchasing raw compute; they are testing autonomous agent workflows in overseas data centers before committing to multimillion-dollar rack deployments.
Sales professionals must prepare for longer evaluation cycles driven by software compatibility checks. When pitching high-cost infrastructure, reps should anticipate questions about migration paths from domestic alternatives and be ready to provide concrete proof-of-concept support rather than relying solely on raw performance metrics.
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