【文章标题】：Open Models are the United Front of AI
【文章标题】：开源模型是AI的统一战线
【文章正文】：
The following is a cross-post from 葬AI / FuneralAI, an uproariously funny Chinese blog about the ups and downs of the AI industry. Check out their many other articles on
以下内容转载自「葬AI/FuneralAI」——一个用荒诞幽默记录AI行业浮沉的中文博客。更多精彩文章请关注其
Substack
Substack
and WeChat Public Accounts!
与微信公众号！
Translation by Fable 5.1 and checked by Irene. Footnotes added to explain some historical references.
由Fable 5.1翻译，Irene校对。部分历史典故已添加注释说明。
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ChinaTalk是读者支持的出版物。欢迎订阅免费或付费计划以获取新文章并支持我们。
These days, the situation is excellent with Chinese models, and new releases take turns to farm Opus 5 like a boss monster.
当下国产模型形势一片大好，新版本如刷副本般轮番挑战Opus 5这个关底BOSS。
1
注1
But we still have to see the situation clearly and should not deceive ourselves
但我们必须清醒认识现状，不可自欺欺人
A theory of quick victory and a theory of defeat are two sides of the same coin, and both are very bad actions.
速胜论与亡国论本是一体两面，皆非善策。
We have to first get the sequence straight. In early June, the evil Anthropic released the powerful Fable 5. Only then did many domestic models with benchmark scores approaching Fable 5 appear.
首先要理清时间线：六月初邪恶的Anthropic放出Fable 5后，国内才涌现出大批对标该水准的模型。
The basic picture, in which OpenAI and Anthropic hold a large lead, has not changed. The premise is that our large models still lag behind; only then can we debate whether the gap is six months or four.
OpenAI与Anthropic大幅领先的基本格局未变。必须承认我们仍处落后地位，才有资格讨论差距是六个月还是四个月。
Whether from the viewpoint of model performance or parameter count, K3 and Qwen 3.8 Max are still a full major generation behind Fable 5, and with GPT 6 about to be released, the gap may widen further.
无论模型表现还是参数量，K3与通义3.8 Max仍落后Fable 5整整一代。随着GPT 6即将发布，差距可能继续拉大。
The progress of the past two months shows up mainly in how much faster domestic models are following up. With the successive releases of GLM 5.2, K3, and Qwen 3.8 Max, we can confirm one basic fact: domestic large models are improving at an accelerating pace, and the gap between open-source and closed-source models is, for now, narrowing.
过去两月的进步主要体现在国产模型跟进速度上。随着GLM 5.2、K3、通义3.8 Max相继发布，我们可确认一个基本事实：国产大模型正在加速进步，开源与闭源模型的差距正在阶段性缩小。
The most critical variable here is open source.
其中最关键的变量正是开源。
Open source has terminated the logic of the theory of defeat. It has replaced “America encircles Chinese AI” with a protracted war in which open source encircles closed source.
开源已终结亡国论的逻辑，将”美帝围剿中国AI”的叙事转变为开源围剿闭源的持久战。
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The logic of the theory of defeat is very simple. America has the largest amount of the most advanced compute, plus OpenAI’s first-mover advantage, and large models are a business where, once the technical path has been proven, things mostly come down to piling on compute and scaling up data.
亡国论的逻辑很简单：美国拥有最多先进算力+OpenAI的先发优势，而大模型赛道技术路线验证后，本质就是堆算力与扩数据。
In terms of compute, Nvidia GPUs shipped to China inevitably suffer losses along the way. In terms of data, the US was also first to build out high-end human annotation. Synthetic data, like using
算力方面，运往中国的英伟达GPU必然折损；数据方面，美国又率先建成高端人工标注体系。像通过
transfer stations
中转站
to hit the Claude API and grind benchmarks, is bound to be lossy too. As long as we respect the law of conservation of energy, Chinese large models cannot possibly catch up to America.
调用Claude API刷榜的合成数据也必有损耗。只要承认能量守恒定律，中国大模型就绝无可能追上美国。
That logical sequence is all correct. But if everything ran on logic, there would be no such thing as entrepreneurship, and everyone would just clock day in and day out to tighten screws.
这套逻辑推演完全正确。但若万事皆循逻辑，世上便不会存在创业，所有人只需日复一日拧螺丝即可。
I put together a timeline of the major open-weight releases of large models.
我整理了大模型开源权重发布的时间轴：
It is obvious at a glance: open-source models have gone from being mostly small experimental models in the early days to, recently, three open-sourced models approaching Opus 5. Open-source performance is closing in on top closed-source models faster and faster.
一目了然：开源模型已从早期的小型实验品，发展为近期三款逼近Opus 5的开源产品。开源性能正以越来越快的速度逼近顶级闭源模型。
Chinese-vendor-led open-sourcing of large models has changed the balance of power between the two sides.
以中国企业为主导的大模型开源改变了双方力量对比。
Open source has enlarged the base of the AI industry and consolidated every AI team outside the closed-source labs into a united front.
开源扩大了AI产业基本盘，将闭源实验室之外的所有AI团队凝聚成统一战线。
The most recent example: the release of K3 triggered a knee-jerk reaction from the US government, which planned to restrict American companies from deploying open-source models. More than 270 tech companies and organizations, including Nvidia and Microsoft, published an open letter supporting open-source models, and then, for now, nothing happened. K3 was not banned.
最新例证：K3发布引发美国政府条件反射式反应，计划限制美企部署开源模型。结果英伟达、微软等270余家科技公司与组织联署公开信支持开源，最终风波暂息——K3未被封禁。
Clearly, if K3 were a closed-source model, this many companies would not have come to its defense; at most Jensen would say a few words to sell GPUs. The whole world under heaven has suffered under Anthropic for a long time. Acting in their own interest, commercial companies will inevitably back open-source models against the evil Italian, to stop the latter from swallowing everything.
显然，若K3是闭源模型，断不会有如此多企业为其辩护——至多黄仁勋为卖GPU说几句漂亮话。天下苦Anthropic久矣，商业公司出于利益考量，必然支持开源模型对抗邪恶意大利人，阻止其鲸吞一切。
We can already see this trend today. Fable 5 is so expensive that even tech giants cannot open it up for unrestricted use by all employees. Everyone uses Fable 5 for a handful of complex jobs, and the vast majority of tasks are done by relatively cheap models. The latter is a ready-made ecological niche for every open-source model.
当下已可见此趋势：Fable 5贵到连科技巨头都无法全员无限制使用。人们仅将其用于少数复杂任务，绝大多数需求则由相对廉价的模型处理——这正是所有开源模型现成的生态位。
What will inevitably happen in the future is that the vast majority of token demand will be served by open-source models, and only a tiny number of complex scenarios will require expensive, strictly moderated closed-source models.
未来必将呈现的图景是：绝大多数token需求由开源模型满足，仅极少数复杂场景需要昂贵且严格审核的闭源模型。
Small open-source models in particular have dramatically changed the meta of the game.
特别是小型开源模型，已彻底改变游戏规则。
Open-source models fully clearing the usability bar and reaching somewhere between Opus 4.6 and 4.8 is something t
开源模型全面突破可用性门槛、达到Opus 4.6至4.8之间的水准，这件事…(下文待续)