如同马拉松比赛中的两艘帆船,开源与闭源 AI 实验室正在旧金山湾中抢风转向、调整航向。
2023 年,闭源模型在 Chatbot Arena Elo1上以巨大优势领先。两年后,DeepSeek R1 时刻到来,这是开源阵营对 ChatGPT 时刻的回应。两艘船并驾齐驱了近一年。
架构改进与首批基于 Blackwell 训练的模型带来了阶跃式变化,从 2026 年起由 GPT-5.2 与 Fable 5 开启。
接下来几周将迎来又一波开源发布潮。月之暗面于 7 月 16 日发布了 Kimi K3,这是一个 2.8T 参数的开源权重模型。阿里巴巴于 7 月 19 日预览了 Qwen 3.8,一个 2.4T 模型。DeepSeek V4将于 7 月中旬从预览版转正。这些紧随Thinking Machines 的 Inkling之后——一个 975B 的 Apache-2.0 多模态模型,于 7 月 15 日发布——以及 Meta Superintelligence Labs 于 4 月推出的 Muse Spark。
开源模型从未在公开水域取得领先,但这或许并非必要。按 90/10 的输入输出比例混合计价,开源权重前沿模型的中位价格比 GPT-5.2 便宜约 15%。最便宜的开源模型 DeepSeek V4 Flash 则便宜约 90%。
我们可能面临这样一种动态:闭源模型推动行业前进,而开源迅速复制以实现商品化。这会拖慢创新吗?
竞争往往会带来相反的效果。OpenAI 已将推理成本削减了 50%。Kimi 发布了全新的注意力架构 KDA。Fable 的阶跃式突破让整个行业都在加倍努力追赶。
业界面临的核心问题是利润率将走向何方。Anthropic 即将公布其首个盈利季度。Bezos 曾说过,你的利润就是我的机会。开源的竞争动态使利润率和定价始终保持竞争性。
AI 浪潮将成为美国有史以来最大的基础设施项目2之一,也很可能是推动经济加速增长的最大贡献者之一。竞争对于保持这场竞赛的高速推进至关重要。
前沿不再是一场单向竞赛。它是一个循环往复的周期:闭源模型领先,开源模型追赶,整个市场加速前进。
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Chatbot Arena Elo 是一套借鉴自国际象棋的评分系统。用户会并排看到两个匿名模型的回复,并为更好的那个投票。每个模型初始分为 1000。战胜更强的模型比战胜更弱的模型获得更多分数;评分差距可以预测对战胜负的概率。100 分的 Elo 差距意味着评分较高的模型约有 64% 的概率获胜。该评分反映的是人类在开放式对话中的偏好,而非推理、编程或智能体基准测试的表现。↩︎
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关于规模估算及其所流经的增长渠道,参见大语言模型对 GDP 的影响。↩︎
Like two sailboats in a marathon race, open & closed AI labs are tacking & jibing in San Francisco Bay.
In 2023, closed source models led by an enormous margin on Chatbot Arena Elo1. Two years later, the DeepSeek R1 moment arrived, the open-source answer to the ChatGPT moment. The two boats raced side-by-side for nearly a year.
Architectural improvements & the first Blackwell-trained models brought a step change with GPT-5.2 & Fable 5 starting in 2026.
The next few weeks will see another flurry of open-source releases. Moonshot shipped Kimi K3, a 2.8T parameter open-weight model, on July 16. Alibaba previewed Qwen 3.8, a 2.4T model, on July 19. DeepSeek V4 graduates from preview in mid-July. These follow Thinking Machines’ Inkling, a 975B Apache-2.0 multimodal model released July 15, & Meta Superintelligence Labs’ Muse Spark in April.
Open-source models have never taken an open-water lead, but that may not be necessary. Blend prices at a 90/10 input-to-output ratio & the median open-weight frontier model runs about 15% cheaper than GPT-5.2. The cheapest open model, DeepSeek V4 Flash, is roughly 90% cheaper.
We may have a dynamic where the closed models drive the industry forward & open-source rapidly copies to commoditize. Will that slow down innovation?
Competition tends to do the opposite. OpenAI has cut inference costs by 50%. Kimi shipped a new attention architecture, KDA. Fable’s step function has an entire industry redoubling to catch up.
The major question put to the industry is what will happen to margins. Anthropic is about to post its first profitable quarter. Bezos said your margin is my opportunity. Open source’s competitive dynamics keep margins & pricing competitive.
The AI wave will be among the largest infrastructure projects2 ever for the US & likely one of the greatest contributors to faster economic growth. Competition is essential to keeping the race fast.
The frontier is no longer a one-way race. It is a repeating cycle: closed models pull ahead, open models catch up, & the whole market moves faster.
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Chatbot Arena Elo is a rating system borrowed from chess. Users see responses from two anonymous models side-by-side & vote for the better one. Each model starts at 1000. Winning against a stronger model earns more points than winning against a weaker one; the gap in ratings predicts the probability of winning a matchup. A 100-point Elo gap implies the higher-rated model wins about 64% of the time. The score reflects human preference on open-ended chat, not reasoning, coding, or agentic benchmarks. ↩︎
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See The GDP Impact of LLMs for the scale estimate & the growth channel it flows through. ↩︎