Tighter Trump-administration restrictions on access to US-made AI models are steering companies—facing rising costs and unpredictable rules—toward open-source models, including those from China.
June 2026 · AI Policy & Markets
US Curbs on Closed AI Models Are Pushing Companies Toward Chinese Open Weights
New export restrictions and release delays on American frontier models are raising costs and uncertainty — ironically accelerating corporate migration to cheaper, less constrained Chinese open-weight models like DeepSeek and Qwen.
~41%
Chinese share of recent open-model downloads, early 2026
700M+
Qwen downloads — the most-downloaded open model family
~80%
of US open-source startups estimated to run Chinese models
Open-model download share, early 2026
Chinese open weights have edged ahead of US models
DeepSeek V4 Pro
License: MITArchitecture: MoE (~49B active of 1.6T)Input: ~$0.435 / M tokensOutput: ~$0.87 / M tokensContext: 128K+Strengths: math, reasoning, coding efficiency
Qwen3 series
License: Open weightsArchitecture: Multiple variantsContext: Up to 1M tokensStrengths: SWE-Bench / agentic, long context, multimodal
Case in point · Lindy
Lindy moved 100% of its traffic from Claude to US-hosted DeepSeek v4 — "a matter of survival."
AI inference costs had exceeded payroll
Switch expected to save millions per year
Why firms switch
Dramatically lower per-token cost
No vendor lock-in; self-host on non-US infrastructure
Permissive MIT / Apache 2.0 licenses
Avoids API fees and US usage limits
The trade-offs
Migration needs real engineering effort
Gaps in nuanced instruction-following
Less English-centric tuning vs top closed models
Geopolitical scrutiny of Chinese-origin tech
The paradox: by restricting closed US frontier models, the clampdown is in effect accelerating the spread of the Chinese open models it sought to counter.
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