A Change in AI Strategy
A Change in AI Strategy
- 1作者判断 AI 模型已进入商品化，7 月以来价格下降 41%、token 用量增长 50%
- 2OpenAI 将 Luna 降价超 80% 争夺份额，前沿模型 token 份额从 8 月的 53% 落至 40% 多
- 3作者建议模型厂商转售第三方模型、控制用户界面并积累路由数据用于后续训练
- 4Ramp 数据显示头部 1% 用户 8 月人均月支出降 9.7% 至 $7,205，自 7 月峰值降温
模型层正走向商品化，竞争重心从基准领先转向分发入口和数据积累，模型厂商的出路在平台化经营。
- 影响：模型调用成本在快速下降，企业可借中小档模型与路由方案压低推理支出；供应商评价标准需要从榜单成绩转向入口能力与数据归属；议价空间随头部厂商互相抢份额而扩大。
- 参考：可考虑重算模型调用预算，把价格降幅与用量增幅放在一起测算净成本变化；值得为路由分类类场景选一个低价决策模型做小规模试点。
- 依据：价格降 41%、用量增 50%、头部 1% 支出回落等数据出自 Ramp AI Index 等第三方口径，商品化判断与三条策略为作者个人分析。
In short : AI models have reached commodity status as prices fall 41% while token usage surges 50%. To win relative share, labs should partner & resell models, control the user interface where distribution becomes the moat, & capture routing data to reduce the cost of training future models.
What if AI models have just reached commodity status? In early 2025, we debated whether labs would become the airlines of the AI industry : high cost, low margin businesses with undifferentiated products.
Over the past month, the evidence has mounted :
- OpenAI cut prices on Luna by more than 80% to win share.1
- Frontier models’ share of tokens slipped from 53% in August into the mid-40s as companies defaulted to smaller, cheaper tiers.2
- Open source demand has shifted decisively from frontier-dominated to medium-&-small tiers.3
- Spending among the top 1% of adopters fell 9.7% in August to $7,205 per employee per month, cooling from its July peak.4
- Decision models like TypeSafe’s Jev are winning share of LLM calls at $0.04 per million input tokens, roughly 75x cheaper than standard LLMs for routing, gating, & classification.5
Throughout all this, token usage has surged 50% since July, while prices have fallen 41%.6
What’s the strategy in this environment?
First, partner. OpenAI announced a partnership with Baseten to resell open-weight models.7 Elon tweeted that the Grok bot would use the best model to complete a task, not just SpaceXSI models.8 Reselling produces a new, high-margin revenue stream by collecting a toll on products without bearing the cost to serve.
No company can provide the best model for every use case. Maximizing customer attention & retention is the most valuable asset in a commodity market.
Second, control the user interface. Distribution has become the moat. Build great harnesses that demand a lot of tokens : give them mononyms like Dots, Bot, & Muse to retain users.9 Also provide the best models for the job so people stay. This suggests ads & commerce as an important revenue driver for the B2C market.
Third, capture user data for intelligent routing & training infrastructure. Reselling other models while routing tasks across them aggregates a tremendous amount of information useful for subsequent model training.
Winning share becomes the only game that matters when aggregate dollar spend cools while token volume compounds. This means controlling the user interface.
OpenAI’s recent surge toward a ~$70b run rate highlights the dynamic : aggressive price cuts & marketplace aggregation allowed it to recapture share within a boat length of Anthropic.10
In a commoditizing market, the spoils do not accrue to the lab with a marginal benchmark lead, but to the platform that aggregates the volume.
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The Most Important Market in AI is the Middle & Segmentation Drives Market Share Wins in AI ↩︎
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ha! 😄 ↩︎
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GP at Theory Ventures. Former Google PM. Sharing data-driven insights on AI, web3, & venture capital.
来源：Tomasz Tunguz 博客 · tomtunguz.com