NVIDIA -11%! Will DeepSeek Drag Computing Demand Down?
$NVIDIA(NVDA)$ opened 11% down, with the market dubbing DeepSeek "the biggest threat to the US stock market."
What’s even more striking is the ultra-low cost of achieving such remarkable results, raising shareholder skepticism about the massive spending by other large models.
DeepSeek-V3 trained a 671 billion-parameter model using only 2,048 H800 GPUs, costing just $5.576 million—significantly lower than the training costs of other top-tier models (e.g., GPT-4 at $1 billion).
NVIDIA and other hardware manufacturers traditionally hold an advantage on the training side, but this development could potentially impact their market position and strategic direction. Some believe DeepSeek may disrupt NVIDIA’s dominance in the AI hardware space.
Will computing power demand increase or decrease?
DeepSeek’s significant impact on NVIDIA’s stock price comes from the implication that its low-cost model could shift the demand for computing power from the training side to the inference side. This means future demand for inference computing power might become the primary driver.
However, some analysts argue that the demand for computing power will not decrease.
For instance, during the First Industrial Revolution, improvements in steam engine efficiency actually led to higher total coal consumption. Similarly, smartphones became affordable and widespread, which drove an increase in total market consumption.
How do you view the impact of DeepSeek?
Is this a short-term or long-term bearish factor for NVIDIA?
At what price are you planning to buy the dip in NVIDIA?
Leave your comments and also post to win tiger coins~
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While DeepSeek’s ability to train a massive model at a fraction of the usual cost raises questions about GPU demand for training, I don’t believe overall computing power demand will decline. History has shown that greater efficiency often leads to more demand, not less—just like steam engines and smartphones.
For NVIDIA, this could be more of a transition than a threat. AI computing is evolving, and inference workloads will still require powerful hardware. If anything, this disruption could accelerate innovation and create new growth opportunities.
As for buying the dip, I’m watching key support levels. If NVIDIA reaches an attractive entry point, I’d consider adding to my position.
@Tiger_comments @TigerStars @TigerGPT
$GRANITESHARES 1.5X LONG NVDA DAILY ETF(NVDL)$
$T-REX 2X LONG NVIDIA DAILY TARGET ETF(NVDX)$
DeepSeek’s significant impact on NVIDIA’s stock price comes from the implication that its low-cost model could shift the demand for computing power from the training side to the inference side. This means future demand for inference computing power might become the primary driver.
However, some analysts argue that the demand for computing power will not decrease.
@TigerGPT @LMSunshine @koolgal @Shyon @Aqa @SPACE ROCKET @GoodLife99 @Universe宇宙 @HelenJanet @rL
How do you view the impact of DeepSeek?
Is this a short-term or long-term bearish factor for NVIDIA?
At what price are you planning to buy the dip in NVIDIA?
Leave your comments and also post to win tiger coins~
Eventually catch up but will need some time . China is really very efficient and dynamic as You can see when visiting the country
但是我个人觉得一个不停想再创新的公司，如果有不错的买入价格，不曾不是一件好事。我昨天开仓英伟达