[RussianCow]

Once you've used a model that runs at hundreds of TPS, it's hard to go back. Everything completes so quickly that you can iterate without breaking out of flow state. My biggest gripe with slow (<50tps) LLMs is that I've lost all the mental context I built up by the time it's done, which makes it extremely difficult to explore or iterate on solutions.

[nmfisher]

Completely agree. Slow but smart models (Fable, Sol, GLM5.2 etc) are great, but they leave me with zero mental model of the code that's been written. Most of the time my mind wanders off and I go check social media or fire off a prompt for some other random project, it's a big productivity drain.

Working with models that are super fast, but slightly dumber (like mimo-v2.5-pro-ultraspeed) is amazing, I feel like I'm still the one that's actually making every decision.

[trollbridge]

Glad to see another UltraSpeed addict here. I really hope they keep it around.

[ngcc_hk]

In 1980s ibm has studied and said why sub-second response needed to maintain the mental flow. That time you send a whole screen unlike unix like character by character. This proves very true even when you deal with form processing. I think that we are dealing with the same issue here.

Keep your mental context in your brain is critical

[hx8]

I'd rather have slower and better output than worse and faster output.

[RussianCow]

It depends. For something high stakes or inherently complex, sure, you don't want to have to clean up the agent's mess afterwards. But for many tasks like building web UIs, the difference in output quality is going to be small enough that iteration speed will win over quality.

With a fast enough model, I can iterate on the UI of a given screen 4-5 times before Opus finishes its first attempt.