I'm also curious to see the details of the models that Dynomight's LLMs produced!
I'm also curious to see the details of the models that Dynomight's LLMs produced!
LLM T(t) Cost
Kimi K2.5 (reasoning) 20 + 52.9 exp(-t/3600)+ 27.1 exp(-t/80) $0.01
Gemini 3.1 Pro 20 + 53 exp(-t/2500) + 27 exp(-t/149.25) $0.09
GPT 5.4 20 + 54.6 exp(-t/2920) + 25.4 exp(-t/68.1) $0.11
Claude 4.6 Opus (reasoning) 20 + 55 exp(-t/1700) + 25 exp(-t/43) $0.61 (eeek)
Qwen3-235B 20 + 53.17 exp(-t/1414.43) $0.009
GLM-4.7 (reasoning) 20 + 53.2 exp(-t/2500) $0.03I'd like to see a sensitivity study to see how much those terms would need to be changed to match within a few %. Exponentials are really tweaky!
I'd be very interested in seeing separate graphs for each major component and how they add up to the total. Even asking the LLMs to separate it out might improve some of their results, would be interesting to try that too.
The evaporative cooling as you pour into the cup is when the coffee is at the highest temperature and has the most surface area even though it only takes a few seconds. One could test this either by including it explicitly in the requested calculation, or by putting the fill spout directly at the bottom of the cup when filling.
dT/dt = -k(T_0 - T_room)
so T(t) = T_room + (T_0 - T_room) exp(-kt)
exp(-x) has a fast drop off then levels off.
scroll down, these graphs just don't look similar.
There is another factor here: convection. Its speed depends on the viscosity of the fluid and the temperature difference both. And viscosity itself depends on the temperature, so you get this very sharp dropoff.
Apparently the act of pouring has a huge effect on temperature because of the surface area :: volume ratio of the fluid as it streams (and turbulence after striking the bottom). The site above claims a single pour can drop it 20-30 degrees. There may be a similar effect here.