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Gemini 3.5 Flash

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Re: Gemini 3.5 Flash

#271

Post by OakNinja »

GodelNumbering wrote: post #84

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

To be fair, Gemini 3.1 flash _lite_ supports structured output (guaranteed json), it’s super fast, runs circles around 2.5 flash and costs $0.25/$1.50.

I use it _a lot_ and it’s very capable if you just plan correctly. I actually almost exclusively use 3.1 flash lite and 2.5 flash lite (even cheaper) and we have 99.5% accuracy in what we do.

That said, I think we’ll see the lite/flash models and the pro models will diverge more price wise. The pro models will become more and more expensive.

Re: Gemini 3.5 Flash

#272

Post by anthonypasq »

LetsGetTechnicl wrote: post #258
roadside_picnic wrote: post #199

Earlier quoted context omitted.

These companies are unprofitable (as all companies at this stage and ambition should be) but I increasingly don't see any justification for the idea that it is fundamentally unprofitable. Inference alone is certainly profitable. I'm running models at home that are comparable to performance of paid models a year or so ago for free. Even for much larger models the cost around inference serving are clearly manageable. T…

If it's profitable, why haven't they reported any profits? People like Ed Zitron have done the math and it just doesn't add up. I mean he just published this piece today: https://www.wheresyoured.at/ai-is-too-expensive/

Amazon was unprofitable for over a decade, and they were public. Theres no incentive to be profitable as a private company if you can continue to raise money.

Ed Zitron and Gary Marcus are... confused.

Re: Gemini 3.5 Flash

#273

Post by Corence »

WarmWash wrote: post #57
aliljet wrote: post #33

Is there a good benchmark tracking hallucinations? The models are all incredibly good now, even the open ones, and my hope is that the rate of hallucinations is something that's falling off in concert with larger and larger context lengths.

People complain about them incessantly, but I can almost never get people to actually post receipts. Every provider allows sharing chats, and anyone can share a prompt that reliably produces hallucinations. More often than not, people are using images in responses that go awry. Which is fair, the models are sold as multi-modal, but image analyses is still at gpt-4.0 text-analyses levels. Also knowledge cutoff issues,…

https://gemini.google.com/share/3717c8505d6b

Two of the three strip titles are hallucinated and two of the three strips are bad examples. Haley is mute in strip 403 and does nothing. Strip 578 is the start of the arc that shows the behavior Gemini is talking about, but has things going wrong so it's not a good example either.

Claude picks a good strip but also hallucinates the strip title: https://claude.ai/share/56be379d-c3da-443e-b60f-2d33c374eba8

Re: Gemini 3.5 Flash

#274

Post by khy »

simonw wrote: post #131

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 sun is very similar to the one from the background of this other top HN post about the OS museum: https://news.ycombinator.com/item?id=48195009

Re: Gemini 3.5 Flash

#275

Post by andriy_koval »

landtuna wrote: post #270
owentbrown wrote: post #228

Has anyone switched from Claude 4.7 Opus or ChatGPT 5.5 to this? How does it feel? Dumber? Worth it for the speed? I'd love someone's subjective take on it, after doing a long session of coding. Reiner Pope gave a talk on Dwarkesh Patel about token economics. I guess faster is a lot more expensive, generally. Someone should make a harness that uses a fast model to keep you in-flow and speed run, and then uses a slow,…

I was using GPT 5.5 for a bunch of work this morning. It's brilliant and efficient. I was also using GPT 5.4 mini. It gets the job done and works great for subtasks that 5.5 designs. Gemini 3.5 Flash is SUCH a Gemini. It seems to work okay, but its attitude is disgusting. "Yes, your idea is excellent." "How this works beautifully:" "This is a fantastic development!" "This is an exceptionally clean and robust architec…

I added something: be grumpy cynical software engineer with strong rigor, and it fixed personality.

Re: Gemini 3.5 Flash

#276

Post by humanfromearth9 »

throwa356262 wrote: post #255
xbmcuser wrote: post #233

Earlier quoted context omitted.

What we need is a deepseek moment in hardware ie China reaching parity on node size that is the only way latest computers let alone latest ai will be available to us in the future otherwise the profit margins will push most production to AI.

To be honest, China not having access to the latest hardware is exactly what has driven LLM technology forward the last 2 years.

Why?

Re: Gemini 3.5 Flash

#278

Post by uejfiweun »

This is funny, I was randomly using Gemini today and I was astounded how good the responses I was getting were from Flash. I guess this must be the reason why.

Re: Gemini 3.5 Flash

#279

Post by [deleted] »

hedgehog wrote: post #136
simonw wrote: post #131

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.

[deleted]

Re: Gemini 3.5 Flash

#280

Post by TurdF3rguson »

spyckie2 wrote: post #222
rudedogg wrote: post #94

Earlier quoted context omitted.

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.

Its probably that in 1 or 2 years local (free) models will completely take the place of cheap models so cheap models need to move up the quality chain. You have free local models for most tasks, $20 subscriptions for near-frontier intelligence, and API per token costs for frontier intelligence. Flash seems to be targeting the near-frontier category.

That might work if it wasn't for FOMO. Are you ok with only $20 of frontier usage a month?
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