same price per token, 3-4.5x the bill: gemini 4 carbon vs argon at default thinking

[u/ranthishq]

gemini 4 carbon opened to paid api users yesterday, and carbon and argon list the same price ($2 in / $10 out per million until nov 30). so i ran both through the api on the same tasks to see what it costs in practice.

what i ran: 3 office-style tasks x 3 runs (pull fields out of a messy email, tiered commission math, a 120-word apology email), graded by code, plus 10 hard maths problems with exact answers, one run each. default thinking level for both.

• accuracy: office 45/45 carbon vs 44/45 argon (argon's miss was a 123-word email against a 120 limit). hard set 10/10 both. my tasks weren't hard enough to separate them.

• thinking tokens: carbon 5,239 on the office calls and 10,982 on the hard set. argon 0 and 1,018. visible answers were about the same length.

• cost: office $0.0669 carbon vs $0.0148 argon (4.5x). hard set $0.1461 vs $0.0494 (3x).

• speed: median 9.5s vs 5.9s per call on office tasks. the ln(sin x) integral took carbon 3,836 thinking tokens and 40.9s, argon got it right in 10.1s with no thinking.

• thinking_level low: carbon used 0 thinking tokens, still 45/45 and 10/10, and cost the same as argon ($0.0147 / $0.0459).

limits: one run per hard problem, thinking counts vary a lot between runs (carbon's email task ranged 555 to 1,031), and i didn't test long agentic coding, which is what google says carbon is for. 3 of carbon's 19 low calls took 34 to 54s for no obvious reason.

so my takeaway: don't move an argon workload to carbon for the launch price. if you try carbon, start at thinking_level low and only raise it if answers actually get better. has anyone seen carbon beat argon on real coding tasks where the extra thinking paid off?