From The Street, July 30:
NVIDIA's Stock Almost Crashes Below $100 After Hours - Then It Surges: Here's Why
It was another miserable day for NVIDIA (Nasdaq: NVDA) as the stock fell 7.04% today. After closing at $103.73, the sell-off continued in after-hours trading, with shares of NVIDIA trading hands for little more than $100 per share.
And then something changed rapidly. NVIDIA shares jumped and are now trading for $109 per share in after-hours trading, a 5% jump from where they closed trading today. Let’s look at why NVIDIA shares lost so much today and then explore why they’re suddenly rebounding so strongly in after-hours trading.
Key Points in This Article
- NVIDIA shares dropped more than 7% today. The losses were primarily attributable to continuing sector rotation out of technology stocks and also fears around the company’s competitive position after it was revealed Apple trained their new AI models on Google’s TPUs.
- In after-hours trading NVIDIA is rebounding due to positive earnings from rival Advanced Micro Devices (NYSE: AMD) and also positive cloud spending comments from Microsoft (Nasdaq: MSFT)....
...Why NVIDIA Shares Sank 7% Today
NVIDIA shares sank 7% today as technology stocks in general struggled. The Nasdaq-100 fell 1.38%. Each day the Nasdaq falls, the important metric to watch is its relative performance to the Russell 2000. If the Russell 2000 is strongly outperforming, that demonstrates continuing ‘sector rotation’ of investors moving out of strategies like large technology stocks and into other areas like small caps or value stocks.
The Russell 2000 gained .35% today, so it outperformed the Nasdaq-100 by 1.73 percentage points, a massive divide between the two major indexes.
However, there was company-specific news that also played into NVIDIA’s decline today. Apple released a large research paper on the creation of their large language models used in the upcoming release of Apple Intelligence. Here’s the relevant section that impacts NVIDIA (emphasis mine):
“The AFM models are pre-trained on v4 and v5p Cloud TPU clusters with the AXLearn framework [Apple, 2023], a JAX [Bradbury et al., 2018] based deep learning library designed for the public cloud. Training is conducted using a combination of tensor, fully-sharded-data-parallel, and sequence parallelism, allowing training to scale to a large number of model parameters and sequence lengths at high utilization. This system allows us to train the AFM models efficiently and scalably, including AFM-on-device, AFM-server, and larger models. AFM-server was trained on 8192 TPUv4 chips provisioned as 8 × 1024 chip slices, where slices are connected together by the data-center network (DCN) [Chowdhery et al., 2022]. Only data-parallelism crosses the slice boundary, other types of state sharding are within-slice only as the within-slice interconnect bandwidth is orders of magnitude higher than the DCN. The sustained model-flop-utilization (MFU) for this training run was approximately 52%. AFM-on-device was trained on one slice of 2048 TPUv5p chips.”
....MUCH MORE
Pre-market NVDA is up $6.68 (+6.44%) at $110.41.
On the other hand the Tensor Processing Units still haven't achieved their promise of 2017:
Watch Out NVIDIA: "Google Details Tensor Chip Powers" (GOOG; NVDA)
We've said NVIDIA probably has a couple year head start but this bears watching, so to speak....
Or 2018
Ahead of Today's NVIDIA Earnings: A Look at One of the Competitors (GOOG; NVDA)
We'll have much more on Google next week but for today the next-gen Tensor Processing Unit....
Or 2023:
Chips: "Google TPU v5e AI Chip Debuts after Controversial Origins"