OpenRouter上最受欢迎的六个模型均来自腾讯、小米、DeepSeek等中国公司，Anthropic的Claude Opus 4.7仅排第七。 Vercel数据显示，6月开源模型处理了平台上近三分之一的AI请求。 Hugging Face CEO认为企业更倾向拥有自己的AI模型，平台每7秒创建一个新仓库。 微软CEO Satya Nadella警告企业应避免单一模型供应商锁定。
这个夏天的几周时间里，人工智能行业都在关注Anthropic最新的前沿模型：https://techcrunch.com/2026/06/09/anthropics-claude-fable-5-is-a-version-of-mythos-the-public-can-access-today/ 以及华盛顿争夺对这些模型访问权的斗争：https://techcrunch.com/2026/06/15/the-us-governments-anthropic-models-ban-was-never-about-an-ai-jailbreak/。但当每个人都在关注前沿模型时，开发者们却一直在构建新产品——而且他们并没有等待Anthropic和OpenAI这类公司的许可。
今年春天，中国的开放权重模型在Hugging Face上的下载量占41%：https://huggingface.co/blog/huggingface/state-of-os-hf-spring-2026，超过了美国的模型。在OpenRouter上：https://openrouter.ai/rankings#top-models，最受欢迎的六个模型全部来自中国公司的开放模型，包括腾讯、小米、DeepSeek、MiniMax和Z.ai。截至本文撰写时，Anthropic的Claude Opus 4.7位居第七。此外，Vercel的数据：https://vercel.com/ai-gateway/leaderboards/labs显示，开放权重模型：https://vercel.com/blog/ai-gateway-production-index-july-2026 正在承担AI应用大量的、流量密集的基础设施负载，而封闭模型则作为更高成本的高端层使用。6月，开放模型处理了平台上近三分之一的AI请求。
这些平台只捕捉了AI生态系统的一部分；尤其是，它们没有包括主要实验室托管的会话，而这些会话很可能占了OpenAI和Anthropic的大部分使用量。但开源模型在市场中越来越大的份额提出了一个难题：如果大多数生产型AI最终运行在成本更低、可定制的替代方案上，前沿模型还有多大意义？
一些人认为，开源模型的增长意味着最智能的模型最终可能只用于最专业化的应用场景。“也许几年以后，前沿模型将用于实验和一些真正高价值的任务，而大多数生产工作负载实际上将由公司内部的私有模型或开源模型提供支持，”Hugging Face首席执行官Clem Delangue在最近一期Equity节目中表示：https://techcrunch.com/podcast/open-source-ai-matters-more-than-ever-according-to-hugging-faces-clem-delangue/。
Hugging Face 是一个以托管、分享并帮助公司部署开源模型而闻名的平台和开发者社区。Delangue 表示，Hugging Face 的客户和社区成员越来越多地宣传拥有自己 AI 模型的好处，而不是租用模型，这一趋势在经历了扩展封闭前沿模型的成本账单的冷酷现实后，进一步加速：https://techcrunch.com/2026/06/05/the-token-bill-comes-due-inside-the-industry-scramble-to-manage-ais-runaway-costs/。
“如果你是一家 AI 公司或科技公司，你不想把核心能力外包给另一家公司，不想依赖你无法控制、看不见、也没有任何所有权的黑箱 API，”Delangue 说。
Delangue 认为，这种转变在 Hugging Face 上的活动中得以体现。据 Delangue 介绍，该平台每七秒就会创建一个新仓库，托管着近三百万个公共模型和一百万个公共数据集。这显示出一种与“一个模型统治一切”的理念不同的图景。他说，实际情况更像是公司使用许多不同的模型，其中许多模型都是为其特定用例定制的。他表示，半数《财富》500 强公司正在使用 Hugging Face 来部署自己的私有模型和开源模型。
开源模型的日益流行正与中国 AI 实验室持续推出越来越强大的新产品同时发生。
每隔几个月，另一家中国 AI 公司就会发布一个强大的开源权重模型，这种模型比封闭竞争对手更便宜、更易定制，从而击破了美国公司投入数十亿美元的专有 AI 模型的经济性。最近，总部位于北京的 AI 公司 Z.ai 发布了一个名为 GLM-5.2 的开源权重模型，该模型在代理编码方面表现出色，并能与 Anthropic 最新模型在识别安全漏洞方面竞争。
Delangue 并不是唯一一位主张企业应避免依赖单一模型供应商的高管。
微软 CEO Satya Nadella 最近警告：https://x.com/satyanadella/status/2076323181154230284?s=46&t=45_xAnRsdQP1GVqYv9Gdbw 避免依赖单一供应商，认为数据控制应成为企业使用 AI 时的首要关注点。
“虽然我们确实需要模型提供商拥有对公共数据进行模型训练的公平使用权所带来的重大创新，但我觉得讽刺的是，现状却是，随后又对模型蒸馏施加限制性条款，并保留从客户使用和互动数据中学习的权利，”纳德拉说道。“如果学习只朝一个方向流动，经济价值就会汇聚到学习基础设施所有者手中，而不是知识本身的创造者手中。因此，把学习基础设施分发给每家公司，使他们能够掌控自己的学习循环，是势在必行的。”
开放模型的兴起也加剧了关于是否应该广泛提供越来越强大的模型的争论。
Anthropic CEO Dario Amodei 曾提出：https://www.techpolicy.press/transcript-senate-hearing-on-principles-for-ai-regulation/，扩展强大的开放模型权重可能变得危险，因为一旦发布，它们就难以控制。其他人：https://www.ibm.com/think/insights/unregulated-generative-ai-dangers-open-source 认为，开放模型更容易被不法分子获取，他们可能用它们传播虚假信息或实施网络或生物战争。
Delangue 对这一权衡有不同看法。
“AI 最大的风险是权力的集中，”Delangue 说道。“在我看来，使世界更安全的方式是平衡竞争环境，并对这些模型建立透明度。”
透明度意味着防御者可以更容易地“修补他们已经知道开放源模型可能利用的网络安全漏洞，”他说道。
这位 Hugging Face 的高管认为，保持强大模型封闭并不能消除高级 AI 系统相关的风险，部分原因是绕过前沿模型 API 的防护措施并窃取权重：https://techcrunch.com/2026/02/23/anthropic-accuses-chinese-ai-labs-of-mining-claude-as-us-debates-ai-chip-exports/ 并公开传播它们很容易。Delangue 认为，限制强大模型，只会将技术集中在少数公司手中，同时减少对系统运作方式的透明度。
“仅仅为少数球员保密，你并不能真正保证安全，”德朗格说。“你让它更危险，因为你制造了权力和能力的不对称。”
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Rebecca Bellan 是 TechCrunch 的高级记者，负责报道塑造人工智能的商业、政策及新兴趋势。她的作品还曾发表于《福布斯》、《彭博社》、《大西洋月刊》、《每日野兽》等刊物。
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Satya Nadella 对使用人工智能的公司发出了令人震惊的警告：https：//techcrunch.com/2026/07/13/satya-nadella-has-issued-a-shocking-warning-to-companies-using-ai/ Julie Bort：https：//techcrunch.com/author/julie-bort/
苹果针对OpenAI商业秘密诉讼中最荒诞的指控：https：//techcrunch.com/2026/07/13/the-wildest-allegations-in-apples-trade-secrets-lawsuit-against-openai/ Sarah Perez：https：//techcrunch.com/author/sarah-perez/
Anthropic开始为印度本地化Claude定价，印度是其仅次于美国的最大市场：https：//techcrunch.com/2026/07/13/anthropic-starts-localizing-claude-pricing-for-india-its-biggest-market-after-the-us/ Jagmeet Singh：https：//techcrunch.com/author/jagmeet-singh/
Meta在引发反弹后删除了Instagram上的有争议AI功能：https：//techcrunch.com/2026/07/10/meta-removes-controversial-ai-feature-on-instagram-after-backlash/ Lucas Ropek：https：//techcrunch.com/author/lucas-ropek/
苹果因涉嫌商业秘密盗窃起诉OpenAI：https：//techcrunch.com/2026/07/10/apple-sues-openai-over-alleged-trade-secret-theft/ Sarah Perez：https：//techcrunch.com/author/sarah-perez/
埃隆·马斯克称赞 Mythos/Fable，承诺不会‘切断’ Anthropic：https://techcrunch.com/2026/07/09/elon-musk-praises-mythos-fable-promises-not-to-cut-off-anthropic/ 朱莉·博特：https://techcrunch.com/author/julie-bort/
Instagram 用户：以下是如何阻止 Meta 的 AI 使用你的照片：https://techcrunch.com/2026/07/09/how-to-stop-metas-ai-image-generator-from-using-your-instagram-photos/ 劳伦·福里斯塔尔：https://techcrunch.com/author/lauren-forristal/
For several weeks this summer, the AI industry was fixated on Anthropic’s latest frontier models：https://techcrunch.com/2026/06/09/anthropics-claude-fable-5-is-a-version-of-mythos-the-public-can-access-today/ and Washington’s fight to control：https://techcrunch.com/2026/06/15/the-us-governments-anthropic-models-ban-was-never-about-an-ai-jailbreak/ who was granted access to them. But while everyone was watching the frontier, developers kept building — and they weren’t waiting around for permission from the Anthropics and OpenAIs of the world.
Chinese open-weight models accounted for 41% of downloads：https://huggingface.co/blog/huggingface/state-of-os-hf-spring-2026 on Hugging Face this spring, surpassing U.S. models. On OpenRouter：https://openrouter.ai/rankings#top-models, the top six most popular models are all open models from Chinese firms, including Tencent, Xiaomi, DeepSeek, MiniMax, and Z.ai. Anthropic’s Claude Opus 4.7 trails in seventh place, at the time of this writing. And data from Vercel ：https://vercel.com/ai-gateway/leaderboards/labsshows that open-weight models：https://vercel.com/blog/ai-gateway-production-index-july-2026 are absorbing much of the volume-heavy infrastructure of AI apps, while closed models operate as the higher-cost, premium layer. Open models handled nearly a third of AI requests on the platform in June.
Those platforms only capture one slice of the AI ecosystem; in particular, they leave out sessions hosted by major labs, which likely account for the bulk of OpenAI and Anthropic’s usage. But open source models’ large and growing share of the market raises a difficult question: How much do frontier models still matter if most production AI ends up running on cheaper, customizable alternatives?
Some see the growth of open source models as a sign that the most intelligent models may end up being used for only the most specialized use cases. “Maybe in a few years, the frontier models will be for experimenting and [for] some really high-value tasks, and most of the production workloads will actually be powered either by private models within companies or by open source models,” Hugging Face CEO Clem Delangue said on a recent episode of Equity：https://techcrunch.com/podcast/open-source-ai-matters-more-than-ever-according-to-hugging-faces-clem-delangue/.
Hugging Face is a platform and developer community best known for hosting, sharing, and helping companies deploy open models. Delangue says Hugging Face’s customers and community members are increasingly touting the benefits of owning their own AI models rather than renting them, a trend that’s picked up steam in the cold light of day after getting the bill associated with the cost of scaling closed frontier models：https://techcrunch.com/2026/06/05/the-token-bill-comes-due-inside-the-industry-scramble-to-manage-ais-runaway-costs/.
“If you’re an AI company or a technology company, you don’t want to outsource your core capabilities to another company, to a black box API that you don’t control, don’t have any visibility on, and don’t really have any sort of ownership,” Delangue said.
That shift, Delangue argues, is reflected in the activity happening on Hugging Face. A new repository is created every seven seconds on the platform, which hosts almost three million public models and one million public datasets, per Delangue. That points to a different picture than the “one model to rule them all,” he says. In reality, it looks more like companies using many different models, many of which are customized for their specific use case. Half of all Fortune 500 firms are using Hugging Face to deploy their own private models and open source models, he says.
The growing popularity of open models coincides with a steady stream of increasingly capable releases from Chinese AI labs.
Every few months, another Chinese AI company releases a powerful open-weight model that is cheaper to deploy and easier to customize than closed competitors, undercutting the economics of proprietary AI that U.S. firms have poured billions into. Most recently, Beijing-based AI company Z.ai released an open-weight model called GLM-5.2 that excels at agentic coding and competes with Anthropic’s latest models on identifying security vulnerabilities.
Delangue isn’t the only executive arguing that enterprises should avoid tying themselves to a single model provider.
Microsoft CEO Satya Nadella recently warned：https://x.com/satyanadella/status/2076323181154230284?s=46&t=45_xAnRsdQP1GVqYv9Gdbw against single provider lock-in, arguing that control of data should be a primary concern for enterprises using AI.
“While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation, and to reserve the right to learn from customer usage and interaction data,” Nadella said. “If learning flows in only one direction, economic value converges toward the owners of the learning infrastructure rather than the creators of the knowledge itself. Therefore, it’s imperative that we distribute the learning infrastructure to every firm so that they can control their own learning loop.”
The rise of open models has also intensified a debate over whether increasingly capable models should be broadly available at all.
Anthropic CEO Dario Amodei has argued：https://www.techpolicy.press/transcript-senate-hearing-on-principles-for-ai-regulation/ that scaling powerful open model weights could become dangerous because once they are released, they become difficult to control. Others：https://www.ibm.com/think/insights/unregulated-generative-ai-dangers-open-source have argued that open models are easier to access by bad actors who could use them to spread disinformation or enact cyber or biological warfare.
Delangue sees the tradeoff differently.
“The biggest risk in AI is concentration of power,” Delangue said. “The way you make the world safer, in my opinion, is by leveling up the playing fields and creating transparency on these models.”
Transparency means defenders can more easily “patch the cybersecurity risks that they already know open source models can exploit,” he said.
The Hugging Face executive argues that keeping powerful models closed doesn’t eliminate the risks associated with advanced AI systems, in part because it’s easy to get past frontier model API guardrails and to steal the weights：https://techcrunch.com/2026/02/23/anthropic-accuses-chinese-ai-labs-of-mining-claude-as-us-debates-ai-chip-exports/ and disseminate them openly. Restricting powerful models, Delangue argues, simply concentrates the technology in the hands of a few companies while reducing transparency into how systems work.
“You don’t really make it safe by keeping it behind closed doors for just a few players,” Delangue said. “You make it more dangerous because you create asymmetry of power and asymmetry of capabilities.”
When you purchase through links in our articles, we may earn a small commission：https://techcrunch.com/techcrunch-affiliate-monetization-standards/. This doesn’t affect our editorial independence.
Rebecca Bellan is a senior reporter at TechCrunch where she covers the business, policy, and emerging trends shaping artificial intelligence. Her work has also appeared in Forbes, Bloomberg, The Atlantic, The Daily Beast, and other publications.
You can contact or verify outreach from Rebecca by emailing rebecca.bellan@techcrunch.com：mailto:rebecca.bellan@techcrunch.com or via encrypted message at rebeccabellan.491 on Signal.
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Satya Nadella has issued a shocking warning to companies using AI：https://techcrunch.com/2026/07/13/satya-nadella-has-issued-a-shocking-warning-to-companies-using-ai/ Julie Bort：https://techcrunch.com/author/julie-bort/
The wildest allegations in Apple’s trade secrets lawsuit against OpenAI：https://techcrunch.com/2026/07/13/the-wildest-allegations-in-apples-trade-secrets-lawsuit-against-openai/ Sarah Perez：https://techcrunch.com/author/sarah-perez/
Anthropic starts localizing Claude pricing for India, its biggest market after the US：https://techcrunch.com/2026/07/13/anthropic-starts-localizing-claude-pricing-for-india-its-biggest-market-after-the-us/ Jagmeet Singh：https://techcrunch.com/author/jagmeet-singh/
Meta removes controversial AI feature on Instagram after backlash：https://techcrunch.com/2026/07/10/meta-removes-controversial-ai-feature-on-instagram-after-backlash/ Lucas Ropek：https://techcrunch.com/author/lucas-ropek/
Apple sues OpenAI over alleged trade secret theft：https://techcrunch.com/2026/07/10/apple-sues-openai-over-alleged-trade-secret-theft/ Sarah Perez：https://techcrunch.com/author/sarah-perez/
Elon Musk praises Mythos/Fable, promises not to ‘cut off’ Anthropic：https://techcrunch.com/2026/07/09/elon-musk-praises-mythos-fable-promises-not-to-cut-off-anthropic/ Julie Bort：https://techcrunch.com/author/julie-bort/
Instagram users: Here’s how to stop Meta’s AI from using your photos：https://techcrunch.com/2026/07/09/how-to-stop-metas-ai-image-generator-from-using-your-instagram-photos/ Lauren Forristal：https://techcrunch.com/author/lauren-forristal/
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