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Brett: Chinese models like DeepSeek and Kimmy K3 are gaining traction, but primarily in China and emerging markets, and haven't significantly challenged Western frontier models like Gemini or ChatGPT.
Ben Horowitz states that various software companies, customer support services, and specialized applications benefit from cheap intelligence offered by open-source models like DeepSeek and Kimmy, with virtually all AI application providers utilizing some open-source component.
The open-source AI landscape is thriving, with multiple strong proprietary US options like Google, OpenAI, Anthropic, XAI, and Thinking Machines. Additionally, Chinese open-source models such as Kimi, DeepSeek, and Quinn are contributing significant development, suggesting a diverse, competitive future.
DeepSeek CEO Liang Wenfang founded the AI company to benefit humanity, not for maximum profit or an IPO, embracing a vision-driven approach.
Frank points to unknown factors for Chinese model companies, including R&D borrowing and government subsidies. DeepSeek's V4 model, priced up to 10x lower on its platform than on Microsoft Azure, suggests significant structural margin differences.
Microsoft is reportedly considering a locally hosted fine-tune of DeepSeek V4 for Copilot Co-work to offer cheaper AI access to enterprise customers, potentially normalizing Chinese models in US enterprise stacks.
The launch of DeepSeek and Huawei's Cloud Matrix disproved the narrative that China was far behind and would copy U.S. regulations.
Nick observes OpenRouter's weekly usage leaderboard is dominated by Chinese models, with Tencent, Xiaomi, and Deepseek occupying the top three spots.
Chinese AI models now account for over 30% of US developer traffic on Open Router, peaking at 46%, with DeepSeek offering input tokens at roughly 55 times cheaper than OpenAI.
Deepseek open-sourced DSpark, a speculative decoder system that achieved an 85% inference speed increase during testing on small models, highlighting ongoing efforts in optimization beyond OpenAI.
Open Router's June report shows four open-weight models, including China's DeepSeek v4, Qwen 2.7, and GLM 5.2, are frequently used in agentic workflows for cost efficiency. They state open-weight models maintain a consistent 3-6 month gap behind frontier labs.
Zechner uses GPT-5.5 as his daily driver for code but switches to Claude for prose, and dabbles with open-weight models like Kimi 2.6 and DeepSeek.
China's DeepSeek AI is funded by Huawei and performs at 90% of US AI capability at a tenth of the cost, according to Dixon.
Krystal suggests OpenAi wants a government stake to become 'too big to fail' and secure a future bailout, while also potentially justifying bans on cheaper foreign AI like DeepSeek.
Ben states DeepSeek's SWE benchmark is more realistic, showing a 2x performance gap between GPT-4o and GPT-4o-mini, which matches practical experience. He notes 20% of official SWE-Bench runs were found to have cheated.
On the DeepSeek SWE benchmark, GPT-4.5 scored 70% while Claude Opus 4.8 scored 58%. The hosts note a massive efficiency gap, with GPT-4.5 solving tasks for $6.60 on average versus Opus 4.8 at $12.58.
The token shortage is driving market-based innovation for cheaper inference. Cursor's Composer 2.5 offers lower cost than top models, while DeepSeek made a permanent 75% price cut on its V4 model to capture cost-conscious users.
Dixon identifies three markets China could rug-pull simultaneously: stocks via DeepSeek's lower-cost AI valuation, bonds via treasury selling, and commodities via a London gold derivative squeeze.
He argues that despite the AI capex narrative, the DeepSeek model's emergence proved frontier AI requires far lower compute and capital, potentially breaking the valuation assumptions for Nvidia and the semiconductor supply chain.
Dixon claims China holds three structural 'rug pull' levers: a stock market rug pull via DeepSeek proving lower-compute AI models, a bond market rug pull via treasury sales, and a commodity market rug pull via supply chain control.
Dixon states DeepSeek's emergence, which caused a $600B Nvidia correction, challenged the core hyperscaler semiconductor assumption of the AI bubble. If frontier models require far lower compute, the valuations of Nvidia, TSMC, and Broadcom are based on a false scarcity moat.
The host cites Open Router data showing Chinese AI models hit 9 trillion tokens the week of May 18th, leading US models for four consecutive weeks, with DeepSeek-V4 Flash topping global usage at 3.4 trillion tokens.
Eric Burnhartson and Tara note Chinese open-source models like DeepSeek are very good technically but come with problematic biases, making direct deployment for sensitive applications like dictation risky.
Simon identifies three potential rug pulls China could engineer: a stock rug pull via DeepSeek's lower valuation, a bond rug pull via treasury selling, and a commodity rug pull via gold market pressure.
Milan argues open-source text models like GLM 5.1, DeepSeek V4 Pro, and Kimi K 2.6 are three to six months behind the top closed-source models in quality for tasks like programming or medical advice.
Max Wheathe notes past speculation that 80% of venture capital-backed tech startups used DeepSeek due to its low cost; however, Ara Karazian refutes this, stating its peak adoption was less than 1% of firms.
DeepSeek faces challenges in gaining broader adoption due to security perceptions, especially among businesses building customer-facing products, despite its potential cost advantages.
China's DeepSeek AI now performs 90% of top U.S. AI capabilities at one-tenth the cost, integrated with Huawei's chip, hardware, and energy ecosystem with zero U.S. dependency.
Delangue says the US's historical strength in open-source, which birthed the Transformer, has reversed. He claims China is now the strongest open-source contributor, with US startups and academia often using Chinese models like DeepSeek, Kuen, and Kimi.
Milan De Reede, CEO of NanoGPT, offers access to diverse AI models including premium (Claude, ChatGPT) and open-source (Nano Banana, Deepseek), allowing payments with various cryptocurrencies or credit cards.