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Truist raises Nvidia stock price target to $307 on strong results

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Truist raises Nvidia stock price target to $307 on strong results

Truist raised its Nvidia price target to $307 from $287 and lifted FY2027 EPS estimates to $12.29 from $11.48, citing accelerating demand, a $3 trillion to $4 trillion AI TAM by 2030, and no evidence of an AI bubble. Nvidia’s revenue was up 65% over the last 12 months, and the company’s latest quarter and outlook beat consensus, with combined April-July guidance of $173 billion in revenue and $3.94 in EPS versus $166 billion and $3.69 expected. Multiple analysts also raised targets, reinforcing positive sentiment around Nvidia’s AI/data center growth and capital returns.

Analysis

The key market message is not that Nvidia is still growing; it is that the stock can likely keep compounding even if growth decelerates meaningfully from here because the ecosystem is still under-penetrated. That matters for a market that has already priced a lot of “AI boom” narrative into the entire semiconductor complex: the real second-order beneficiaries are the firms selling picks-and-shovels into the buildout, while the losers are lower-quality AI hardware names that need flawless execution just to justify multiple expansion. What looks most interesting is the widening gap between fundamental momentum and valuation skepticism. When a franchise can re-accelerate at scale, raise capital returns, and still be treated as “expensive,” the stock often keeps working until demand visibility breaks rather than until the multiple looks cheap. The bigger risk is not a classic bubble burst; it is a sequencing problem where capex pauses for one or two quarters, causing the market to extrapolate peak growth too early and compressing the entire AI supply chain in sympathy. The consensus may still be underestimating how concentrated the upside is in time. Over the next 3-6 months, positive revisions and tighter supply should continue to support the shares, but over a 12-18 month horizon, law-of-large-numbers risk becomes the main constraint and any slowdown in hyperscaler ordering could trigger a fast de-rating. That creates a favorable setup for using near-term momentum, while hedging the longer-dated multiple risk with structures that benefit from both continued upside and eventual exhaustion.