Yes—the US–China gap in leading AI model performance narrowed sharply, and Stanford HAI said it had effectively closed in its 2026 AI Index. But that is a finding about model performance, not proof that China has overtaken the United States across AI. DeepSeek’s benchmark breakthrough was an important moment in the shift; later results and other measures of national strength tell a more complicated story.
What the latest model comparisons show
Stanford HAI’s 2026 AI Index reports that US and Chinese models traded the lead multiple times from early 2025, describing their performance gap as effectively closed. The Index places Anthropic’s top model 2.7% ahead as of March 2026. That is a dated comparison between leading models—not a live ranking for October 2026, and not a verdict on every AI capability.
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What DeepSeek changed—and what it did not
A benchmark moment, not a permanent tie
Stanford HAI says DeepSeek-R1 briefly matched the top US model in February 2025. The result helped show that Chinese labs could produce models competitive with the leading US systems. It does not mean DeepSeek remained tied with the top model after that date, or that one benchmark settles which country is ahead.
Why different evaluations can disagree
A benchmark tests a defined set of tasks under a particular setup. Rankings can change with the model version and evaluation date, as well as with what the test measures—such as reasoning, coding, user preference or security. Stanford’s comparison and NIST’s later evaluation are different snapshots using different methods, so they should not be collapsed into one timeless leaderboard.
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What NIST found when it tested DeepSeek models
In an evaluation announced September 30, 2025, the National Institute of Standards and Technology’s Center for AI Standards and Innovation (CAISI) tested three DeepSeek versions and four US reference models across 19 benchmarks. NIST said DeepSeek V3.1 trailed the best US reference model on almost every benchmark in that evaluation. This bounded result does not invalidate Stanford’s account of a narrowing frontier-model gap: it concerns specified model versions and tests at a different point in time.
- Software engineering and cyber tasks: NIST reported that the best US model it evaluated solved over 20% more tasks than DeepSeek V3.1.
- Cost on performance tests: Across 13 performance benchmarks, NIST said one US reference model cost 35% less on average than the best DeepSeek model to perform at a similar level. This is an evaluation-specific comparison, not a general cost advantage for all US models or deployments.
- Simulated agent hijacking: Agents based on DeepSeek R1-0528 were, on average, 12 times more likely than the evaluated US frontier models to follow malicious instructions in NIST’s simulated tests. This measures behavior in those simulations, not the frequency of real-world incidents.
- Jailbreak test: Under a common jailbreak technique, NIST reported that DeepSeek R1-0528 responded to 94% of overtly malicious requests, compared with 8% for the US reference models. Those percentages apply to that specific test.
AI leadership depends on what is being measured
Model scores are only one axis. Stanford HAI reports that the United States produces more top-tier models and higher-impact patents. China leads in the volume of AI publications, citations and patent output. These measures describe different kinds of activity; patent quantity, for example, is not interchangeable with patent impact.
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Compute infrastructure, investment and adoption also matter. A country’s ability to train a leading model does not by itself establish the scale of its broader computing resources or how widely AI is used across its economy. In an October 6, 2025 note, the Federal Reserve said comparisons are complicated by limited transparency in Chinese AI data and different approaches to investment and adoption. As Johns Hopkins SAIS senior fellow Samm Sacks put it in an Associated Press report on September 15, 2026: “The gap between U.S. and Chinese models is narrow and fragile.”
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What business adoption data can—and cannot—tell you
Ramp Economics Lab reported in July 2026 that 5.8% of AI-spending businesses in its customer sample used model-serving platforms in June, up from 4.5% in January. Those platforms provide access to multiple models, and Ramp describes their use as an imperfect proxy for adoption of open-source and Chinese models. The figures are not DeepSeek’s share of the US market, nor a census of businesses across the country.
Rank #3
- EVOLUTION RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 128GB pool, which is perfect for running LLMs such as Deepseek 70B Q8, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 12% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
What “BI Says” means here
The specific Business Insider article named in the supplied headline could not be verified, so its publication date, wording, supporting figures and rationale cannot be confirmed. The underlying claim of a narrowing US–China model-performance gap is independently supported by Stanford HAI’s 2026 Index, but no quotation or additional claim should be attributed to Business Insider on that basis.
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