alt Hacker NewsWhats interesting to note, as someone who uses Gemini, ChatGPT, and Claude, is that Gemini consistently uses drastically fewer tokens than the other two. It seems like gemini is where it is because it has a much smaller thinking budget.
It's hard to reconcile this because Google likely has the most compute and at the lowest cost, so why aren't they gassing the hell out of inference compute like the other two? Maybe all the other services they provide are too heavy? Maybe they are trying to be more training heavy? I don't know, but it's interesting to see.
Replies
They have to have SOME competitive advantage. What reason is there to use Gemini over Claude or ChatGPT? It's not producing nearly the quality of output.
They just released their enterprise agentic platform today so my expectation is that might be the gravity well for the Fortune 500's to park their inference on.
I'm 50% convinced that the main lift in GLM-5 over GLM-4.7 was that it was much more willing to use tokens. I had the hardest time getting 4.7 to read enough source code to actually know what it was doing, but once I convinced it to read, it was pretty capable.
Being thrifty can be good! But it also can mean your system is not reflecting sufficiently, is not considering enough factors, isn't reading enough source code.
We are still firmly in "who really knows" territory. I have mixed feelings about token spendiness vs thrift, is all.
I've been trying Gemini Pro using their $20-ish Goole One subscription for a couple of months, and I also find it consistently does fewer web searches to verify information than say ChatGPT 5.4 Pro which I have through work.
I was planning on comparing them on coding but I didn't get the Gemini VSCode add-in to work so yeah, no dice.
The Android and web app is also riddled with bugs, including ones that makes you lose your chat history from the threads if you switch between them, not cool.
I'll be cancelling my Google One subscription this month.