--- type: "source" source_kind: "article" title: "AI Economics in the East: Part 2" "source url": "https://www.mbi-deepdives.com/ai-economics-in-the-east-part-2/?ref=mbi-deep-dives-newsletter" author: - "[[MBI Deep Dives]]" published: 2026-04-15 captured: "2026-04-15T16:45:18-04:00" status: "inbox" description: "Yesterday, Flo Crivello tweeted something that caught my attention:We've tested new OSS models the moment they're released for a while at Lindy. Inference is our #1 cost by a lot (more than payroll) — cutting it by 2-5x would be transformative.Last year, OSS models were \"not even close.\"3" tags: - "reference" topics_auto: entities_auto: related_auto: distilled_to: used_in: --- ## AI Distillation --- clipped_from: https://www.mbi-deepdives.com/ai-economics-in-the-east-part-2/?ref=mbi-deep-dives-newsletter clipped_date: 2026-04-15T16:45:18-04:00 title: AI Economics in the East: Part 2 tags: article, summary, AI --- **Thesis:** Open-source AI models are now competitive with frontier models for most use cases, drastically reducing inference costs. This shift threatens the high-profit margins of frontier labs, similar to pharmaceutical patents with limited exclusivity periods. Consequently, companies relying on frontier models may face valuation pressures, and the long-term availability of advanced models via APIs is uncertain. **Key Mechanisms / Ideas:** - Open-source vs. closed-source model performance gap - Inference cost as a major expense - Pharmaceutical-like profit squeeze cycles - Scale advantages in training budgets (e.g., $100B runs) - API pricing and economic models - Valuation multiples for AI companies - Strategic role of Chinese AI labs (Zhipu, MiniMax) **Why This Is Important:** Strategically, this affects business decisions on model adoption, cost efficiency, and competitive positioning in AI-driven products. Intellectually, it challenges notions of sustained monopolistic advantages, prompting analysis of innovation cycles, market concentration, and the democratization of AI technology. **Open Questions:** - How permanent is the open-source gap closure, and will frontier models maintain an edge through scale? - What are the long-term implications for API economics and valuation multiples of AI companies? - Weaknesses include reliance on speculative analysis and limited empirical data on cost-performance trends. - Areas needing further thought: regulatory impacts, geopolitical factors in AI development, and sustainability of open-source ecosystems. ## Full Content Yesterday, Flo Crivello [tweeted](https://x.com/Altimor/status/2044108104816832576?ref=mbi-deepdives.com) something that caught my attention: > We've tested new OSS models the moment they're released for a while at Lindy. Inference is our #1 cost by a lot (more than payroll) — cutting it by 2-5x would be transformative. > > Last year, OSS models were "not even close." > > 3 months ago, "almost there." Came close to making Kimi K2.5 our default. > I think we are right now crossing the line to "at the frontier, for most use cases." GLM-5.1 in particular is incredible and will likely be our default soon. > Surprised by this development — OSS caught up. For context, here’s the head-to-head on Anthropic’s Claude Opus 4.6 and Zhipu’s GLM-5.1 flagship model API pricing (per million tokens): ![](https://substackcdn.com/image/fetch/$s_!VjbJ!,w_2400,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F3e4901a6-b5b5-4292-a00b-6016d84eb843_1107x340.png) Source: KoyFin (MBI Deep Dives readers get 20% discount; just click here ) Rohit Krishnan [captured](https://x.com/krishnanrohit/status/2044123219926372672?ref=mbi-deepdives.com) how strong open source models can change the economics in AI (emphasis mine): > “I think a most fundamental open question today is this - how much the open to closed source gap will continue to exist. If it does, and it's perpetual per model, **we have a concentrated pharma like future for frontier labs.** They have 6/13/18/24 months to squeeze the profits before it gets competed away. > > The default amount of profit is not zero either, since not everyone can create a model. But **it's not going to be 60% gross margin inference if Zhipu can compete for it.** > > Now, it's possible there are some things where the open-to-close gap is longer. Claude's personality maybe as an example. Not everyone will care, but some will! And for them this is the price vector that matters. So a consumer business here can probably continue to command due to brand and utility. > > And **if the frontier models truly hit a scale where OS can't reach, say $100B training runs, then they can have more enduring advantage**. Revenues can grow, expenses can become more about maintenance and sustainability, and usage changes. You'd use the best possible model to do the thing you want to, or to explore, and for anything that's settled, a workflow, you'd get that done for much cheaper with the lowest cost model possible. > > **Which means the distribution of future profits are either highly crunched (few years to squeeze) or long tail (for exploration and super smart work**). It'd be interesting to see how this plays out, and what it means for how to price the OpenAI/ Anthropic IPO.” The more I think about it, the less likely it appears that the most advanced models will be available via API in the long-term (see yesterday’s [**piece**](https://www.mbi-deepdives.com/frontier-ais-economic-engine/) for more on this). Given this context, if a company’s product directly competes against frontier model developers’ first-party products in which using the most advanced models would lead to differentiated product experience, multiple for those companies’ earnings **should be** under pressure. Considering how the Chinese models remain deeply relevant in the question of long-term economics of AI over the world, I am going to follow closely the two publicly listed AI labs in the East. I have already covered [Zhipu](https://www.mbi-deepdives.com/ai-economics-in-the-east/) a couple of days ago, and today I will discuss MiniMax which also IPO-ed early this year. The stock has nearly tripled since its IPO and is currently worth ~$40 Billion Enterprise Value (EV). Like Zhipu, the stock is richly valued as it trades at ~180x NTM revenue. I will discuss more about their economics behind the paywall. ![chart](https://substackcdn.com/image/fetch/$s_!YWG_!,w_2400,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F65d515fa-58da-40ff-aa11-ccc0224c04ca_2400x1240.png) Source: KoyFin (MBI Deep Dives readers get 20% discount; just click here ) --- *In addition to “Daily Dose” (yes, **DAILY**) like this, MBI Deep Dives publishes one Deep Dive on a publicly listed company every month. You can find all the 67 Deep Dives* [*here*](https://www.mbi-deepdives.com/models/)*.* ---