1. DeepSeek's technical positioning and business boundaries.
DeepSeek is a Chinese company focused on AGI (general artificial intelligence), with technical characteristics including:
Open-source models: Launching models like DeepSeek-MoE and DeepSeek-V2, partially competing with Llama and GPT, but the parameter scale and performance have not yet reached the level of GPT-4.
API services and commercialization: Providing model calls through API (similar to OpenAI), but mainly targeting Chinese scenarios, with limited market coverage.
Differentiated competition: Focus on lightweight models in vertical fields (such as finance and education), rather than directly challenging the absolute performance of general large models.
Conclusion: DeepSeek's current core business (open-source models, vertical scene optimization) is in misaligned competition with OpenAI (closed-source general large models) and NVIDIA (hardware infrastructure), with weak substitutability in the short term.
2. Potential impact on OpenAI.
Threat level:
Challenges of open-source models: DeepSeek's open-source model may attract part of the developer ecosystem, but OpenAI's core advantage lies in the technological gap of closed-source models (such as the multimodal capabilities and reasoning performance of GPT-4) and commercialization capabilities (enterprise-level API, Microsoft ecosystem binding).
Specialty of the Chinese market: DeepSeek's optimization in Chinese scenarios may divert some of OpenAI's Chinese users, but OpenAI's global market dominance (especially in English scenarios) is difficult to shake in the short term.
Stock price logic:
OpenAI's valuation depends on its technological leadership and commercialization speed. If DeepSeek proves that its open-source model can significantly reduce corporate costs (such as through lightweight deployment), it may raise market doubts about OpenAI's high pricing strategy, but a significant drop in stock prices would require two conditions to be met:
- DeepSeek's technology directly benchmarks OpenAI's performance (not yet achieved);
- The customer loss rate of OpenAI shows an irreversible trend (no data support yet).
3. Potential impact on NVIDIA.
Demand-side logic:
Training phase: DeepSeek's model training still relies on NVIDIA GPUs (such as H100/A100), and its technological development may increase computing power demand rather than decrease it.
Inference phase: If DeepSeek's model optimization technology (such as MoE architecture) significantly reduces inference computing power demand, it may affect the sales of NVIDIA's mid-to-low-end chips (such as T4), but the demand for high-end chips (H100) is supported by the trend of model complexity.
Supply-side logic:
NVIDIA's moat lies in the CUDA ecosystem and the advanced process chip supply chain. Even if Chinese companies (like Huawei Ascend) attempt to substitute, it is difficult to break through the ecological barriers in the short term, and DeepSeek still relies on NVIDIA hardware.
Conclusion: The impact of DeepSeek on NVIDIA is more likely to be structural (such as changing some demand distribution) rather than a systemic shock.
4. The 'symbiosis' of the industry ecosystem.
The essence of current competition in the AI industry is ecological competition, not a single technology showdown:
Binding of OpenAI and NVIDIA: The stronger OpenAI's model, the more it needs NVIDIA's computing power; the more advanced NVIDIA's hardware, the better it can support OpenAI's technological iteration.
The ecological role of DeepSeek:
If DeepSeek promotes more companies to use AI with lower barriers, it could expand the overall AI market size, indirectly benefiting OpenAI (model demand) and NVIDIA (computing power demand).
If its open-source model forms an independent ecosystem, it may divert some developers, but it is difficult to disrupt the core barriers of existing giants.
5. Historical references and market expectations.
Insights from Meta (Llama): After Meta open-sourced the Llama series, the demand for OpenAI's API was not significantly affected, but rather the overall industry growth was driven by ecological prosperity.
Specialty of the Chinese market: Policy restrictions (such as the U.S. chip ban) may give DeepSeek an advantage in the Chinese market, but the global market is still dominated by OpenAI/NVIDIA.
6. Final conclusion.
In the short term, the rise of DeepSeek will not lead to a significant drop in the stock prices of NVIDIA or OpenAI for the following reasons:
1. Insufficient technical substitutability: DeepSeek has not yet surpassed OpenAI's technological gap and does not threaten NVIDIA's hardware monopoly.
2. The cumulative effect of market demand: The expansion of AI application scenarios will simultaneously increase the demand for computing power (NVIDIA) and models (OpenAI).
3. The depth of ecological binding: The partnerships between OpenAI and Microsoft, and NVIDIA with global cloud providers are difficult to be disrupted by regional challengers.
Long-term risk points:
If DeepSeek achieves a paradigm breakthrough in AGI technology paths (such as a new architecture that does not require large-scale computing power), it could change industry rules.
Geopolitical factors lead to a complete separation of AI ecosystems between China and the U.S., with DeepSeek forming a closed loop in the Chinese market (but NVIDIA/OpenAI's global foundation remains solid).
In short, DeepSeek is currently a 'participant' in the AI wave rather than a 'disruptor', and the industry landscape has not yet reached a critical point for qualitative change.
