Nvidia closed April 24 at $208.27 — an all-time high — and crossed the $5 trillion market cap mark. For context: that is more than the combined GDP of Brazil, Mexico, and Argentina. And the detail that matters for anyone creating with AI is another: each Blackwell GPU costs around $40,000 and production is sold out through mid-2026.
The data center division alone generated $62.3 billion last fiscal quarter, up 75% year over year.
What this means for inference pricing
When the sole supplier of top-tier GPUs has a six-month backlog, three things happen:
- Hyperscalers (AWS, Azure, GCP) negotiate priority access and pass on the cost
- Inference APIs stay flat or rise slightly
- Smaller labs run out of enterprise GPUs and migrate to AMD MI400 or Google Cloud TPU
For anyone building workflows on OpenAI or Anthropic API today, this means: current pricing is probably the floor for the next 12 months.
The real competitive pressure
The bull case for Nvidia depends on keeping the monopoly. The bear case has three fronts:
- AMD MI400 series with 432 GB of HBM4 arriving within 10-30% of Blackwell performance
- Hyperscaler custom chips (TPU, Amazon Trainium, Meta MTIA)
- Specialized startups (Groq, Cerebras, Tenstorrent) carving specific niches
If any sign of market-share erosion shows up in the next earnings, Nvidia's multiple compresses fast.
For creators
Nothing changes today. Everything in 12-18 months. But it is worth keeping a contingency model (Claude Sonnet, GPT-4o-mini) for non-critical workloads.
Sources
- CNBC (April 24, 2026): Nvidia hits $5 trillion market cap as AI chip rally continues
- Intellectia: Nvidia 5 Trillion Market Cap April 2026
- CNBC (April 17, 2026): Nvidia AI chip rivals attract record funding as competition heats up