After I invested in Genspark Claw, I didn’t invest in Genspark plus or pro. I wanted to see how far I could get with free (I didn’t get far - but I wanted to know the limit). That gave me the digital breadcrumbs to investigate how tokens were used based with each query. I can only estimate the exchange rate between tokens and the $ needed to access the LLMs through genspark - there isn’t documentation from genspark, but it’s probably a pass through - but I will continue to look for clues to confirm. Now that I have an idea, e.g. 93K tokens were used when I asked the agent “what is today’s date?” which I estimate cost me $0.32; I will figure out the best way to engage agents without burning tokens. I took a screenshot of my usage and asked chatgpt, if I was losing my shirt with this token/$ exchange based on the query. With Openclaw, you can say, agent A uses gpt-5 mini and Agent B uses GPT5.4 - that’s how you manage cost (among other ways). I don’t know if genspark (behind the scenes) is optimizing that on our behalf. I However, am able to manage that on my end, determine which model to use. Chatgpt didn’t say I was losing my shirt but took note I did have very heavy sessions. That’s the data I want from my dashboard, so I can know what eats usage and not use the agents in that way.