231–240 of 692 posts
Yikes. I think the concept of a 'flash' model is changing, no? Google used to market this as its lower-intelligence, faster, cheaper option. I appreciate that they are delivering on both of those, but personally I would appreciate if they could create an incremental knowledge improvement while holding price steady. Fortune 500 companies have to make their money I guess.
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We need another "Deepseek moment" or else it will become impossible for the regular dude to use AI. It will become something that only big companies can afford.
gemini isn't even that good. just tested 3.5 on usual complex prompts to opus/chat 5.5. meh
Per million input/output tokens: Gemini 2.5 flash: $0.30/$2.50 Gemini 3.0 flash preview: $0.50/$3.00 Gemini 3.5 flash: $1.50/$9.00 Interesting pricing direction. I don't think we have ever seen a 3x price increase for in the immediate next same-sized model (and lol @ 3 only ever getting a preview). 3.5 flash costs similar to Gemini 2.5 pro which was $1.25/$10
We need another "Deepseek moment" or else it will become impossible for the regular dude to use AI. It will become something that only big companies can afford.
Can anyone who has extensive, recent, experience with Claude code and Codex contextualize the current Gemini CLI product experience?
Gemini Pro 3.1 for agentic coding is still clumsy. It chews a lot, has a harder time with tools and interacting with the codebase. I haven't tried any 3.5 version, yet, though. The benchmarks look promising.
I'll note I like the Google models' prose better than any others at the moment, though. Even the small open models (Gemma 4 family) have excellent prose, relatively speaking, that doesn't stink of the LLMisms that I find so annoying about OpenAI (especially) and Anthropic models. So, I'll probably start using Gemini for writing API docs, even if all code is Claude.
Yikes. I think the concept of a 'flash' model is changing, no? Google used to market this as its lower-intelligence, faster, cheaper option. I appreciate that they are delivering on both of those, but personally I would appreciate if they could create an incremental knowledge improvement while holding price steady. Fortune 500 companies have to make their money I guess.
Yikes. I think the concept of a 'flash' model is changing, no? Google used to market this as its lower-intelligence, faster, cheaper option. I appreciate that they are delivering on both of those, but personally I would appreciate if they could create an incremental knowledge improvement while holding price steady. Fortune 500 companies have to make their money I guess.
The pelican is a lot : https://github.com/simonw/llm-gemini/issues/133#issuecomment... Not a great bicycle though, it forgot the bar between the pedals and the back wheel and weirdly tangled the other bars. Expensive too - that pelican cost 13 cents: https://www.llm-prices.com/#it=11&ot=14403&sel=gemini-3.5-fl...
That pelican looks like it's in Miami for a crypto conference.
No one talking about how this flash Beats Pro? Imagine what 3.5 pro looks like? Also concerned about Gemini models being benchmaxxed generally
> concerned about Gemini models being benchmaxxed generally I would say they are the least benchmaxxed out of all the top labs, for coding. They've always been behind opus/gpt-xhigh for agentic stuff (mostly because of poor tool use), but in raw coding tasks and ability to take a paper/blog/idea and implement it, they've been punching above their benchmarks ever since 2.5. I would still take 2.5 over all the "chinese…
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If Google is actually getting cheaper inference than everyone else with their TPUs, this smells like trouble to me. Maybe serving LLMs at a profit is proving difficult. Or maybe they think because their benchmarks are good they can ramp up the prices. Seems like they don’t have the market share to justify a move like that yet to me.
This is not priced at inference cost. My guess: it's the price at which they make more money than if they rent the TPUs to other companies. The Gemini team has had trouble securing enough TPUs for their user's needs. They struggle with load and their rate limits are really bad. Maybe at a higher price, they have a better chance at getting more TPUs assigned?
Just because you are vertically integrated doesn't mean you get to discount the one business units products to the other. Doing so discounts the opportunity cost you pay and is just bad accounting.