Famed technology investor Gavin Baker just made the case that cheaper AI models could be the biggest gift possible to the picks-and-shovels crowd. In a post on X, Baker argued that if market share shifts from frontier labs with 90%-plus inference margins toward cheaper open-source models, “margin dollars would effectively get redistributed from the frontier labs to AI infrastructure providers.”
That would put the benefit squarely in the lane of NVIDIA (NASDAQ: NVDA | NVDA Price Prediction), Micron Technology (NASDAQ: MU), and SanDisk (NASDAQ: SNDK), the companies selling the chips, memory, and storage behind the AI buildout. Hyperscalers like Amazon (NASDAQ: AMZN) and Microsoft (NASDAQ: MSFT) could also benefit if cheaper intelligence lowers the cost of serving customers and expands demand.
NVIDIA is up 13.71% year to date to $212.77. A path to $300 in 2027 hinges on the bull case laid out below.
Wall Street Is Already Bullish, but the Bar Can Go Higher
NVIDIA just posted $81.61 billion in Q1 FY2027 revenue, up 85.2% year over year, with Data Center revenue climbing 92% YoY. Non-GAAP EPS of $1.87 topped estimates, extending the company’s earnings beat streak to five straight quarters. Management guided Q2 revenue to $91.0 billion and disclosed $119 billion in supply commitments, pointing to demand visibility and a supply chain buildout unlike anything in company history.
Baker’s Thesis: Cheap Tokens = More GPUs and Memory
Baker’s key point is that cheaper models drive incremental token demand. As inference costs collapse (the cost of inference has dropped a thousand-fold in three years), volume explodes. That volume runs on NVIDIA silicon paired with High Bandwidth Memory.
Micron’s Cloud Memory segment hit $13.77 billion in Q3 FY2026 revenue with gross margins of 84.6%. SanDisk’s Datacenter segment exploded 645% year over year to $1.47 billion. Hyperscaler capex validates the demand: Amazon is planning roughly $200 billion in 2026 capex, and Microsoft’s Q3 FY26 capex hit $30.88 billion, up 84%.
Nvidia CEO Jensen Huang’s point lands in the same place as Baker’s: “Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries.”
The Math on $300
At $212.77, NVIDIA trades around 41x trailing earnings. FY2026 non-GAAP EPS came in at $4.77, and current momentum, with revenue growth above 70% for consecutive quarters, gives Wall Street room to keep raising forward estimates. Shares hitting $300 would require roughly 41% upside from here. Historically, NVDA has cleared that hurdle many times in prior cycles.
The Bottom Line on $300
Baker’s framework flips the “cheap AI kills the bull case” fear on its head. If open source wins, infrastructure providers capture the margin. With a 100% beat rate over five quarters, a next earnings date of August 26, 2026, and hyperscaler capex still accelerating, $300 in 2027 remains ambitious, but the blueprint is there.
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