The Trump administration is expected to prohibit the use of the Chinese AI chatbot DeepSeek on U.S. government devices due to national security concerns, according to a Friday report by the Wall Street Journal, which cited unnamed sources.
DeepSeek AI, the Chinese AI lab that behind the chatbot and its controversial reasoning AI model DeepSeek R1 has positioned itself as an alternative to OpenAI’s ChatGPT and Google’s Gemini.
Citing concerns over data security and potential foreign influence, officials are evaluating whether to prohibit its use on government devices and explore broader restrictions, such as banning DeepSeek from app stores and cloud service providers.
The move would follow similar measures taken against other Chinese technology firms, marking another escalation in the U.S.-China tech rivalry.
The scrutiny of DeepSeek is part of a wider effort to regulate foreign AI applications. The U.S. Navy banned DeepSeek AI on January 29, 2025, citing cybersecurity risks, and Texas followed on February 3, adding the chatbot to its list of restricted applications for state agencies.
Congressional discussions on February 6 raised the possibility of a broader ban, reflecting increasing concerns that Chinese AI models could be used for surveillance or misinformation.
DeepSeek’s Role in China’s AI Ecosystem
DeepSeek AI is one of China’s most prominent chatbots, positioned as a direct competitor to OpenAI and Google. Its rapid adoption within China’s highly controlled tech environment has raised concerns among U.S. regulators, who worry about potential state oversight and its role in shaping global AI narratives. These concerns were heightened when OpenAI banned multiple China-linked AI accounts.
Washington’s fears over AI misuse extend beyond DeepSeek. A Google security report found that state-backed cybercriminals are increasingly using AI-powered phishing tools and deepfake-based deception techniques. These revelations have fueled arguments for stricter AI regulations, particularly concerning models developed in China.
U.S. Expands AI and Semiconductor Restrictions
The U.S. approach to DeepSeek aligns with its broader strategy to curb China’s technological capabilities. In 2023, the U.S. banned Nvidia’s A100 and H100 AI chips from being exported to China, citing national security risks. By 2025, restrictions were tightened further, blocking the sale of A800 and H800 models that had been designed to comply with earlier rules.
With access to these high-performance chips restricted, Chinese firms turned to alternative solutions. DeepSeek and other AI developers have begun stockpiling Nvidia’s H20 chips, one of the last remaining AI processors still legally available under existing U.S. trade rules. However, industry experts speculate that the H20 could be Washington’s next target, further tightening China’s ability to train large AI models.
Microsoft Warns of Fallout from AI Export Controls
Not all U.S. tech leaders agree with the government’s approach. Microsoft has expressed concerns that excessive restrictions on AI chip exports could harm U.S. businesses while failing to prevent China from advancing its AI capabilities.
Microsoft President Brad Smith warned that “AI will continue to spread globally. No single country, including the United States, can stop this. The question is not whether AI will spread, but whether the United States and its closest allies will remain at the forefront of its development.”
While U.S. officials argue that limiting AI hardware sales is necessary for national security, Microsoft and other companies worry that China will accelerate its efforts to develop domestic AI processors. This could ultimately lead to less reliance on U.S. technology while limiting American firms’ ability to compete in global markets.
China’s Response and Retaliation Against U.S. Tech Policies
As Washington tightens controls on Chinese AI firms, Beijing has begun retaliating against American tech giants. A key example is China’s antitrust investigation into Google, which many analysts see as a direct response to escalating U.S. trade policies.
While Google has been absent from China’s search market for years, the company continues to operate through its Android ecosystem and cloud services, making it vulnerable to regulatory pressure from Chinese authorities.
In addition to targeting U.S. companies, China has also taken steps to safeguard its AI industry from foreign interference. On March 1, 2025, the Chinese government imposed new travel restrictions on AI executives, preventing key figures in the sector from visiting the U.S. due to concerns about intellectual property security.
The move underscores China’s strategy of shielding its AI research from potential external threats as tensions with Washington continue to rise.
At the same time, China is doubling down on its own AI development efforts. A new generation of entrepreneurs, sometimes referred to as China’s “Fantastic Four”, is leading the country’s push toward AI self-sufficiency – Liang Wenfeng, founder of Hangzhou-based DeepSeek, along with Wang Xingxing, Zhang Yiming and Wang Tao, the founders of Unitree Robotics, ByteDance and DJI, respectively.
Their work is seen as critical to reducing reliance on U.S. technology, especially in the wake of increasing semiconductor restrictions.
DeepSeek’s Response to Growing Regulatory Pressure
Faced with mounting scrutiny, DeepSeek is accelerating its strategy to solidify its position in the AI market. The company recently fast-tracked the release of its R2 AI model, a development that had originally been planned for a later launch. By pushing forward with the release, DeepSeek aims to reinforce its competitive standing against OpenAI, Anthropic, and Alibaba, all of which are ramping up their AI capabilities.
The decision to expedite the R2 model comes amid concerns that a U.S. ban could limit DeepSeek’s global expansion efforts. If Washington moves forward with further restrictions, the company could face hurdles in reaching international markets, despite strong demand for AI models that can compete with Western alternatives.
The Future of AI Regulation and Global AI Competition
The DeepSeek case highlights a much larger debate over how AI should be regulated and which countries will lead its development. If the U.S. decides to restrict or ban DeepSeek, it could set a precedent for how other foreign AI models are treated in Western markets.
There is already speculation that Washington may expand its regulatory focus beyond DeepSeek, targeting additional AI applications with potential ties to Chinese technology firms.
The geopolitical battle over AI dominance is growing more complex. The U.S. argues that restricting China’s access to AI tools is a national security necessity, while China sees these actions as efforts to stifle its technological rise. The result is an increasingly fragmented AI ecosystem, where government-imposed barriers may shape the future of innovation as much as technological breakthroughs themselves.
AI Model Benchmarks – LLM Leaderboard
Last updated: Mar 16, 2025Benchmark stats come from the model providers, if available. For models with optional advanced reasoning, we provide the highest benchmark score achieved.
| Organization | Model | Context | Parameters (B) | Input $/M | Output $/M | License | GPQA | MMLU | MMLU Pro | DROP | HumanEval | AIME’24 | SimpleBench | Model |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| openai | o3 | 128,000 | – | – | – | Proprietary | 87.70% | – | – | – | – | o3 | ||
| anthropic | Claude 3.7 Sonnet | 200,000 | – | $3.00 | $15.00 | Proprietary | 84.80% | 86.10% | – | – | – | 80.00% | 46.4% | Claude 3.7 Sonnet |
| xai | Grok-3 | 128,000 | – | – | – | Proprietary | 84.60% | – | 79.90% | – | – | 93.30% | Grok-3 | |
| xai | Grok-3 Mini | 128,000 | – | – | – | Proprietary | 84.60% | – | 78.90% | – | – | 90.80% | Grok-3 Mini | |
| openai | o3-mini | 200,000 | – | $1.10 | $4.40 | Proprietary | 79.70% | 86.90% | – | – | – | 86.50% | 22.8% | o3-mini |
| openai | o1-pro | 128,000 | – | – | – | Proprietary | 79.00% | – | – | – | – | 86.00% | o1-pro | |
| openai | o1 | 200,000 | – | $15.00 | $60.00 | Proprietary | 78.00% | 91.80% | – | – | 88.10% | 83.30% | 40.1% | o1 |
| Gemini 2.0 Flash Thinking | 1,000,000 | – | – | – | Proprietary | 74.20% | – | – | – | – | 73.30% | 30.7% | Gemini 2.0 Flash Thinking | |
| openai | o1-preview | 128,000 | – | $15.00 | $60.00 | Proprietary | 73.30% | 90.80% | – | – | – | 44.60% | 41.7% | o1-preview |
| deepseek | DeepSeek-R1 | 131,072 | 671 | $0.55 | $2.19 | Open | 71.50% | 90.80% | 84.00% | 92.20% | – | 79.80% | 30.9% | DeepSeek-R1 |
| openai | GPT-4.5 | 128,000 | – | – | – | Proprietary | 71.4% | 90.0% | – | – | 88.0% | 36.7% | 34.5% | GPT-4.5 |
| anthropic | Claude 3.5 Sonnet | 200,000 | – | $3.00 | $15.00 | Proprietary | 67.20% | 90.40% | 77.60% | 87.10% | 93.70% | 16.00% | 41.4% | Claude 3.5 Sonnet |
| qwen | QwQ-32B-Preview | 32,768 | 32.5 | $0.15 | $0.20 | Open | 65.20% | – | 70.97% | – | – | 50.00% | QwQ-32B-Preview | |
| Gemini 2.0 Flash | 1,048,576 | – | – | – | Proprietary | 62.10% | – | 76.40% | – | – | 35.5% | 18.9% | Gemini 2.0 Flash | |
| openai | o1-mini | 128,000 | – | $3.00 | $12.00 | Proprietary | 60.00% | 85.20% | 80.30% | – | 92.40% | 70.00% | 18.1% | o1-mini |
| deepseek | DeepSeek-V3 | 131,072 | 671 | $0.27 | $1.10 | Open | 59.10% | 88.50% | 75.90% | 91.60% | – | 39.2% | 18.9% | DeepSeek-V3 |
| Gemini 1.5 Pro | 2,097,152 | – | $2.50 | $10.00 | Proprietary | 59.10% | 85.90% | 75.80% | 74.90% | 84.10% | 19.3% | 27.1% | Gemini 1.5 Pro | |
| microsoft | Phi-4 | 16,000 | 14.7 | $0.07 | $0.14 | Open | 56.10% | 84.80% | 70.40% | 75.50% | 82.60% | Phi-4 | ||
| xai | Grok-2 | 128,000 | – | $2.00 | $10.00 | Proprietary | 56.00% | 87.50% | 75.50% | – | 88.40% | 22.7% | Grok-2 | |
| openai | GPT-4o | 128,000 | – | $2.50 | $10.00 | Proprietary | 53.60% | 88.00% | 74.70% | – | – | 17.8% | GPT-4o | |
| Gemini 1.5 Flash | 1,048,576 | – | $0.15 | $0.60 | Proprietary | 51.00% | 78.90% | 67.30% | – | 74.30% | Gemini 1.5 Flash | |||
| xai | Grok-2 mini | 128,000 | – | – | – | Proprietary | 51.00% | 86.20% | 72.00% | – | 85.70% | Grok-2 mini | ||
| meta | Llama 3.1 405B Instruct | 128,000 | 405 | $0.90 | $0.90 | Open | 50.70% | 87.30% | 73.30% | 84.80% | 89.00% | 23.0% | Llama 3.1 405B Instruct | |
| meta | Llama 3.3 70B Instruct | 128,000 | 70 | $0.20 | $0.20 | Open | 50.50% | 86.00% | 68.90% | – | 88.40% | 19.9% | Llama 3.3 70B Instruct | |
| anthropic | Claude 3 Opus | 200,000 | – | $15.00 | $75.00 | Proprietary | 50.40% | 86.80% | 68.50% | 83.10% | 84.90% | 23.5% | Claude 3 Opus | |
| qwen | Qwen2.5 32B Instruct | 131,072 | 32.5 | – | – | Open | 49.50% | 83.30% | 69.00% | – | 88.40% | Qwen2.5 32B Instruct | ||
| qwen | Qwen2.5 72B Instruct | 131,072 | 72.7 | $0.35 | $0.40 | Open | 49.00% | – | 71.10% | – | 86.60% | 23.30% | Qwen2.5 72B Instruct | |
| openai | GPT-4 Turbo | 128,000 | – | $10.00 | $30.00 | Proprietary | 48.00% | 86.50% | – | 86.00% | 87.10% | GPT-4 Turbo | ||
| amazon | Nova Pro | 300,000 | – | $0.80 | $3.20 | Proprietary | 46.90% | 85.90% | – | 85.40% | 89.00% | Nova Pro | ||
| meta | Llama 3.2 90B Instruct | 128,000 | 90 | $0.35 | $0.40 | Open | 46.70% | 86.00% | – | – | – | Llama 3.2 90B Instruct | ||
| qwen | Qwen2.5 14B Instruct | 131,072 | 14.7 | – | – | Open | 45.50% | 79.70% | 63.70% | – | 83.50% | Qwen2.5 14B Instruct | ||
| mistral | Mistral Small 3 | 32,000 | 24 | $0.07 | $0.14 | Open | 45.30% | – | 66.30% | – | 84.80% | Mistral Small 3 | ||
| qwen | Qwen2 72B Instruct | 131,072 | 72 | – | – | Open | 42.40% | 82.30% | 64.40% | – | 86.00% | Qwen2 72B Instruct | ||
| amazon | Nova Lite | 300,000 | – | $0.06 | $0.24 | Proprietary | 42.00% | 80.50% | – | 80.20% | 85.40% | Nova Lite | ||
| meta | Llama 3.1 70B Instruct | 128,000 | 70 | $0.20 | $0.20 | Open | 41.70% | 83.60% | 66.40% | 79.60% | 80.50% | Llama 3.1 70B Instruct | ||
| anthropic | Claude 3.5 Haiku | 200,000 | – | $0.10 | $0.50 | Proprietary | 41.60% | – | 65.00% | 83.10% | 88.10% | Claude 3.5 Haiku | ||
| anthropic | Claude 3 Sonnet | 200,000 | – | $3.00 | $15.00 | Proprietary | 40.40% | 79.00% | 56.80% | 78.90% | 73.00% | Claude 3 Sonnet | ||
| openai | GPT-4o mini | 128,000 | – | $0.15 | $0.60 | Proprietary | 40.20% | 82.00% | – | 79.70% | 87.20% | 10.7% | GPT-4o mini | |
| amazon | Nova Micro | 128,000 | – | $0.04 | $0.14 | Proprietary | 40.00% | 77.60% | – | 79.30% | 81.10% | Nova Micro | ||
| Gemini 1.5 Flash 8B | 1,048,576 | 8 | $0.07 | $0.30 | Proprietary | 38.40% | – | 58.70% | – | – | Gemini 1.5 Flash 8B | |||
| ai21 | Jamba 1.5 Large | 256,000 | 398 | $2.00 | $8.00 | Open | 36.90% | 81.20% | 53.50% | – | – | Jamba 1.5 Large | ||
| microsoft | Phi-3.5-MoE-instruct | 128,000 | 60 | – | – | Open | 36.80% | 78.90% | 54.30% | – | 70.70% | Phi-3.5-MoE-instruct | ||
| qwen | Qwen2.5 7B Instruct | 131,072 | 7.6 | $0.30 | $0.30 | Open | 36.40% | – | 56.30% | – | 84.80% | Qwen2.5 7B Instruct | ||
| xai | Grok-1.5 | 128,000 | – | – | – | Proprietary | 35.90% | 81.30% | 51.00% | – | 74.10% | Grok-1.5 | ||
| openai | GPT-4 | 32,768 | – | $30.00 | $60.00 | Proprietary | 35.70% | 86.40% | – | 80.90% | 67.00% | 25.1% | GPT-4 | |
| anthropic | Claude 3 Haiku | 200,000 | – | $0.25 | $1.25 | Proprietary | 33.30% | 75.20% | – | 78.40% | 75.90% | Claude 3 Haiku | ||
| meta | Llama 3.2 11B Instruct | 128,000 | 10.6 | $0.06 | $0.06 | Open | 32.80% | 73.00% | – | – | – | Llama 3.2 11B Instruct | ||
| meta | Llama 3.2 3B Instruct | 128,000 | 3.2 | $0.01 | $0.02 | Open | 32.80% | 63.40% | – | – | – | Llama 3.2 3B Instruct | ||
| ai21 | Jamba 1.5 Mini | 256,144 | 52 | $0.20 | $0.40 | Open | 32.30% | 69.70% | 42.50% | – | – | Jamba 1.5 Mini | ||
| openai | GPT-3.5 Turbo | 16,385 | – | $0.50 | $1.50 | Proprietary | 30.80% | 69.80% | – | 70.20% | 68.00% | GPT-3.5 Turbo | ||
| meta | Llama 3.1 8B Instruct | 131,072 | 8 | $0.03 | $0.03 | Open | 30.40% | 69.40% | 48.30% | 59.50% | 72.60% | Llama 3.1 8B Instruct | ||
| microsoft | Phi-3.5-mini-instruct | 128,000 | 3.8 | $0.10 | $0.10 | Open | 30.40% | 69.00% | 47.40% | – | 62.80% | Phi-3.5-mini-instruct | ||
| Gemini 1.0 Pro | 32,760 | – | $0.50 | $1.50 | Proprietary | 27.90% | 71.80% | – | – | – | Gemini 1.0 Pro | |||
| qwen | Qwen2 7B Instruct | 131,072 | 7.6 | – | – | Open | 25.30% | 70.50% | 44.10% | – | – | Qwen2 7B Instruct | ||
| mistral | Codestral-22B | 32,768 | 22.2 | $0.20 | $0.60 | Open | – | – | – | – | 81.10% | Codestral-22B | ||
| cohere | Command R+ | 128,000 | 104 | $0.25 | $1.00 | Open | – | 75.70% | – | – | – | 17.4% | Command R+ | |
| deepseek | DeepSeek-V2.5 | 8,192 | 236 | $0.14 | $0.28 | Open | – | 80.40% | – | – | 89.00% | DeepSeek-V2.5 | ||
| Gemma 2 27B | 8,192 | 27.2 | – | – | Open | – | 75.20% | – | – | 51.80% | Gemma 2 27B | |||
| Gemma 2 9B | 8,192 | 9.2 | – | – | Open | – | 71.30% | – | – | 40.20% | Gemma 2 9B | |||
| xai | Grok-1.5V | 128,000 | – | – | – | Proprietary | – | – | – | – | – | Grok-1.5V | ||
| moonshotai | Kimi-k1.5 | 128,000 | – | – | – | Proprietary | – | 87.40% | – | – | – | Kimi-k1.5 | ||
| nvidia | Llama 3.1 Nemotron 70B Instruct | 128,000 | 70 | – | – | Open | – | 80.20% | – | – | – | Llama 3.1 Nemotron 70B Instruct | ||
| mistral | Ministral 8B Instruct | 128,000 | 8 | $0.10 | $0.10 | Open | – | 65.00% | – | – | 34.80% | Ministral 8B Instruct | ||
| mistral | Mistral Large 2 | 128,000 | 123 | $2.00 | $6.00 | Open | – | 84.00% | – | – | 92.00% | 22.5% | Mistral Large 2 | |
| mistral | Mistral NeMo Instruct | 128,000 | 12 | $0.15 | $0.15 | Open | – | 68.00% | – | – | – | Mistral NeMo Instruct | ||
| mistral | Mistral Small | 32,768 | 22 | $0.20 | $0.60 | Open | – | – | – | – | – | Mistral Small | ||
| microsoft | Phi-3.5-vision-instruct | 128,000 | 4.2 | – | – | Open | – | – | – | – | – | Phi-3.5-vision-instruct | ||
| mistral | Pixtral-12B | 128,000 | 12.4 | $0.15 | $0.15 | Open | – | 69.20% | – | – | 72.00% | Pixtral-12B | ||
| mistral | Pixtral Large | 128,000 | 124 | $2.00 | $6.00 | Open | – | – | – | – | – | Pixtral Large | ||
| qwen | QvQ-72B-Preview | 32,768 | 73.4 | – | – | Open | – | – | – | – | – | QvQ-72B-Preview | ||
| qwen | Qwen2.5-Coder 32B Instruct | 128,000 | 32 | $0.09 | $0.09 | Open | – | 75.10% | 50.40% | – | 92.70% | Qwen2.5-Coder 32B Instruct | ||
| qwen | Qwen2.5-Coder 7B Instruct | 128,000 | 7 | – | – | Open | – | 67.60% | 40.10% | – | 88.40% | Qwen2.5-Coder 7B Instruct | ||
| qwen | Qwen2-VL-72B-Instruct | 32,768 | 73.4 | – | – | Open | – | – | – | – | – | Qwen2-VL-72B-Instruct | ||
| cohere | Command A | 256,000 | 111 | $2.50 | $10.00 | Open | – | 85.00% | – | – | – | – | – | Command A |
| baidu | ERNIE 4.5 | – | – | – | – | – | 75.00% | – | 79.00% | 87.00% | 85.00% | ERNIE 4.5 | ||
| Gemma 3 1B | 128,000 | 1 | – | – | Open | 19.20% | 29.90% | 14.70% | – | 32.00% | – | – | Gemma 3 1B | |
| Gemma 3 4B | 128,000 | 4 | – | – | Open | 30.80% | 46.90% | 43.60% | – | – | – | – | Gemma 3 4B | |
| Gemma 3 12B | 128,000 | 12 | – | – | Open | 40.90% | 65.20% | 60.60% | – | – | – | – | Gemma 3 12B | |
| Gemma 3 27B | 128,000 | 27 | – | – | Open | 42.40% | 72.1% | 67.50% | – | 89.00% | – | – | Gemma 3 27B | |
| qwen | Qwen2.5 Max | 32,768 | – | 59.00% | – | 76.00% | – | 93.00% | 23.00% | – | Qwen2.5 Max | |||
| qwen | QwQ 32B | 131,000 | 32.8 | Open | 59.00% | – | 76.00% | 98.00% | 78.00% | – | QwQ 32B |
