Chamath @ 00:59:15Inconclusive
aitech
Over the next few years, frontier foundational AI models will converge in capabilities such that they become near‑interchangeable commodities from the user’s perspective (a “consumer surplus”), with only marginal performance differences between major providers.
Foundational models are quickly becoming a consumer surplus. Every model is roughly the same. They keep getting better and better, but they're also approaching these asymptotic returns.View on YouTube
Explanation
As of November 30, 2025, it’s too early to definitively judge a prediction framed as happening "over the next few years," since only ~17 months have passed since June 29, 2024.
Evidence is mixed:
- Partial capability convergence at the top: Comparative benchmarks often show leading proprietary LLMs (e.g., GPT‑4o/4.1, Claude 3.5/3.7, Gemini 1.5/2.x) clustered closely in performance. For example, GPT‑4o and Claude 3.5 Sonnet achieve very similar accuracy on a medical reasoning benchmark, while open‑source Llama‑3.1‑405B trails but is not dramatically worse. (arxiv.org) A geospatial benchmark finds GPT‑4o and Claude Sonnet 3.5 essentially sharing the top tier. (arxiv.org) This supports a trend toward narrowing gaps among frontier proprietary models.
- Continuing leapfrogging and non‑trivial gaps: Newer releases like GPT‑4.1/4.5, Claude 4.x/4.5 and Gemini 3 Pro still show material performance differences and regularly overtake one another on specific benchmarks (coding, multimodal reasoning, etc.), contradicting a clear plateau of "asymptotic" returns. (reuters.com)
- Systematic differences by vendor: A large 2025 study comparing 18 models from OpenAI, Anthropic, Google, and DeepSeek found clear, statistically significant differences between vendors and model families, concluding that model choice is not neutral. (arxiv.org)
- Economic/UX signals of commoditization, but not full interchangeability: Token prices have dropped sharply (e.g., GPT‑4o mini at $0.15 per million input tokens), and analysts describe foundation models as facing commoditization pressure with low customer lock‑in. (en.wikipedia.org) Yet developers still report distinct practical behavior and preferences among GPT‑4.1, Claude, and Gemini for tasks like coding, indicating models are not perceived as interchangeable. (reddit.com)
Overall, there are early signs of convergence and growing consumer surplus, but frontier models have not yet clearly become near‑interchangeable commodities, and the forecast period is not over. Hence the prediction’s accuracy is inconclusive (too early to call).