Why one Nvidia bull thinks things look ‘spectacular’ heading into the AI chipmaker’s earnings
The Nvidia (NVDA) bulls continue to defend their favorite stock in the world heading into the chipmaker’s earnings report next week.
Despite DeepSeek’s challenge to thinking about AI costs, some analysts are staying upbeat on Nvidia. However, that comes with a few notes of caution — in particular, about a first quarter outlook that may not satisfy elevated market expectations.
“Near-term dynamics are fluid (January quarter to July quarter) … while long-term (October quarter and onward) our work suggests looks frankly spectacular,” Loop Capital analyst Ananda Baruah wrote in a client note on Wednesday.
Baruah reiterated a $175 price target on Nvidia, which assumes 25% upside from current levels.
Added Baruah, “Big picture we believe that two to three year Street numbers remain low as our work with both customers and the Nvidia build ecosystem points [to] … Nvidia GPU reaching 10 million to 12 million as hyperscalers look to increase their percentage on non-CPU compute to 50% plus in coming years (from ~10% currently). Remember … for Nvidia the story is accelerated compute + Gen AI, which means it is facing two $1.0 trillion compute market opportunities ahead of it in coming years, each of which is just at the very start.”
Nvidia stock was up less than 1% in premarket trading at $140 each.
At close: February 19 at 4:00:00 PM EST
While Nvidia shares have rallied back about 23% from the early February lows, sentiment on the company’s fundamentals has become more mixed.
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Evercore analyst Mark Lipacis wrote in a recent note that there are three reasons for the more cautious tone: 1) DeepSeek lowering AI demand in aggregate, 2) DeepSeek shifting AI compute cycles away from Nvidia GPUs and to ASICs [custom chips], and 3) Blackwell chip delays.
China-based DeepSeek surprised markets in late January after unveiling RI, its AI model that gives a ChatGPT-esque performance at a cheaper price tag. RI cost a reported $5.6 million to build a base model, compared with the hundreds of millions of dollars incurred at US-based companies such as OpenAI and Anthropic.
Fears mounted instantly that US companies are overspending on AI infrastructure, which includes Nvidia chips.
“Conventional wisdom all of last year was that training amazing models was going to be possible for only a handful of companies,” Snowflake (SNOW) CEO Sridhar Ramaswamy told me on Yahoo Finance’s Opening Bid podcast. “What DeepSeek has done over the past few weeks is shatter that belief by saying they can train a model for $6 million.”
