Dmytro Kharkov

Nvidia stock stabilizes at $179 amid H200 chip sales restart in China

Nvidia stock stabilizes at $179 amid H200 chip sales restart in China
Nvidia restarts H200 chip production for China

​Nvidia shares continue to consolidate within the current range. As of March 20, Nvidia stock is trading at $179.17, down 0.7% over the past 24 hours. Investors demonstrate higher risk aversion after February’s sharp rally toward $195.

Highlights

  • Nvidia stock is consolidating near $179, and a range-bound phase has been formed between $175 support and $182 resistance.
  • The company has restarted H200 AI chip production for China, signaling a partial recovery in its China business with a moderate impact on long-term growth.
  • Near-term price direction will depend on a breakout from the current range, with upside toward $188–195 or downside risk toward $170 if support fails.

Nvidia’s price action has shifted from the upper trend into a clearly defined consolidation channel. Over the past three weeks, the stock has formed lower highs that confirm bearish pressure. It regularly finds support near the $175–176 zone. However, no long-term structural changes can be identified at the present moment.

The 50-day moving average is now shifting around $180. Price is stabilizing around this average. It typically signals indecision and range-bound trading. Meanwhile, the 200-day moving average remains significantly lower near $150. This confirms that the longer-term uptrend is still intact despite the recent pause.

Nvidia shares price performance (January 2026 – March 2026). Source: TradingView.

Resistance is clearly established at $182, with stronger supply emerging between $185 and $187 where several rallies have reversed in the past. On the downside, immediate support sits at $175. It is followed by a more critical floor at $170. A break below $170 may result in a deeper correction in the long term.

China restart highlights limited but strategic recovery

Nvidia is restarting production of its H200 chip for China after securing export licenses from the U.S. government. The company received confirmed orders from local customers. CEO Jensen Huang stated that manufacturing resumed several weeks ago. The move reflects a partial normalization of operations, but a full reopening of the China pipeline has not been implemented yet.

At the same time, Beijing has reportedly approved the H200 for purchase by Chinese companies. This confirms the fact that demand remains high despite geopolitical instability. The combination of U.S. export clearance and Chinese buyer approval creates a narrow channel for Nvidia to re-enter the market with compliant products. However, the H200 is based on older Hopper architecture. This indicates that Nvidia is not deploying its most advanced technology in China.

Importantly, these China-related sales are not included in Nvidia’s projection of over $1 trillion in revenue. This mostly comes from its next-generation Blackwell and Rubin chips by 2027. This trend implies that while China remains strategically relevant, it is no longer central to Nvidia’s long-term growth potential. Instead, the restart of H200 production should be viewed as moderate upside and a stabilizing factor for revenue diversification.

Outlook suggests imminent breakout from narrow range

In a bullish scenario, a sustained move above $182—particularly with rising volume—would likely trigger momentum buying and open the path toward $188 and then a retest of the $195 high. This would require continued positive news flow, either from demand signals or further easing of geopolitical constraints.

The base case remains sideways consolidation, and the stock may remain between $175 and $185 levels. Meanwhile, investors accumulate prior gains and await the next earnings cycle. This scenario reflects equilibrium between the company’s fundamentals and current valuation.

Nvidia introduced the Vera Rubin platform, integrating seven chips into a unified AI infrastructure. The system, anchored by the NVL72 configuration, will optimize large-scale AI workloads by addressing key bottlenecks across compute, networking, and data processing.

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