Even Sam Altman himself thinks we’re in a bubble, and he ought to have a good sense of the wind direction here.
I think the contradiction here can be reconciled by how these tests don’t tend to run on the typical hardware constraints they need to be able do this at scale. And herein lies a large part of the problem as far as I can tell; in late 2024, OpenAI realized they had to rethink GPT-5 since their first attempt became too costly to run. This delayed the model and when it finally released, it was not a revolutionary update but evolutionary at best compared to o3. Benchmarks published by OpenAI themselves indicated a 10% gain over o3 for God knows how much cash and well over a year of work. We certainly didn’t have those problems in 2023 or even 2024.
DeepSeek has had to delay R2, and Mistral has had to delay Mistral 3 Large, teased within weeks back in May. No word from either about what’s going on. DS is said to move more to Huawei and this is behind a delay but I don’t think it’s entirely clear it has nothing to do with performance issues.
It would be more strange to _not_ have people speculate about stagnation or bubbles given these events and public statements.
Personally, I’m not sure if stagnation is the right word. We’re seeing a lot,of innovation in toolsets and platforms surrounding LLM’s like Codex, Claude Code, etc. I think we’ll see more in this regard and that this will provide more value than the core improvements to the LLM’s themselves in 2026.
And as for the bubble, I think we are in one but mostly because the market has been so incredibly hot. I see a bubble not because AI will fall apart but because there are too many products and services right now in a golden rush era. Companies will fail but not because AI suddenly starts failing us but due to saturation.