This is the AI leaders-vs-laggard basket
Source: zerohedge, Bloomberg
🚨 The AI race is entering a new phase.
Not because demand is slowing. Because costs are becoming impossible to ignore. Here are the numbers: 📈 Chinese AI models now process ~18.5 trillion tokens per week on OpenRouter. 🇺🇸 US models? Around 6 trillion. That's a 3x gap. Why? • Lower energy costs. • More efficient models. • Aggressive pricing that's reshaping the competitive landscape. Meanwhile, something interesting is happening inside large enterprises. Companies including Amazon, Walmart, Cisco, Uber, and Meta are reportedly introducing internal limits on AI usage as spending exceeds expectations. One striking example: A software company saw its AI bill jump 7x overnight after moving from a flat-rate subscription to usage-based pricing. Suddenly, the true cost of AI became visible. And this is only the beginning. 📊 Goldman Sachs estimates AI agents could increase token consumption by 24x by 2030. That creates a fundamental challenge: AI demand may keep exploding... while AI budgets become increasingly constrained. The next competitive advantage won't just be building the smartest models. It will be building the most cost-efficient ones. The AI story is evolving: ➡️ From "Who has the biggest model?" ➡️ To "Who delivers the lowest cost per useful output?" The winners of the next AI wave may not be those with the most compute... ...but those who make intelligence affordable at scale. Do you think AI spending is finally reaching a reality check, or is this just a temporary pause before the next investment wave? Source: FT, Global Markets Investors
There are 2 markets currently 1) The AI stocks; 2) The sources of funds to buy the AI stocks
This scatterplot chart below shows that earnings do matter for AI-themed stocks, but for the rest of the Technology universe, earnings really don't matter YTD. Source: Konstantin Fominykh
While oil's trajectory dominated most of the headlines, a rough weekend for Dario Amodei left Anthropic's Tokenized Stock down notably on the day...
Source: zerohedge
Who owns Anthropic
Stocks World @anandchokshi19
OpenAI is reportedly considering drastic price cuts on its token costs to compete with Anthropic for users
Source: WSJ
S&P 500 ex AI vs. S&P 500 5-day change
That is the biggest spread since AI was birthed... Source: zerohedge, Bloomberg
This chart is comparing how different AI models perform on a set of benchmark tests — mainly around coding, reasoning, and knowledge tasks.
The key takeaway: Claude Mythos 5 / Fable 5 is claiming better performance than GPT-5.5 and Gemini 3.1 Pro on these specific benchmarks. Example: SWE-Bench Pro (agentic coding): Claude: 80.3% GPT-5.5: 58.6% Gemini 3.1 Pro: 54.2% What does that actually mean? “Agentic coding” This measures how well an AI can: understand a software engineering task, navigate codebases, edit files, debug issues, and complete coding workflows autonomously. So higher % = the model solved more real-world coding tasks correctly.
