[HN Gopher] Making 2.5 Flash and 2.5 Pro GA, and introducing Gem...
___________________________________________________________________
Making 2.5 Flash and 2.5 Pro GA, and introducing Gemini 2.5 Flash-
Lite
Author : meetpateltech
Score : 244 points
Date : 2025-06-17 16:06 UTC (6 hours ago)
(HTM) web link (blog.google)
(TXT) w3m dump (blog.google)
| remus wrote:
| I mean the model names are always a bit odd, but flash-lite is
| particulary good!
| candiddevmike wrote:
| Curious to hear what folks are doing with Gemini outside of the
| coding space and why you chose it. Are you building your app so
| you can swap the underlying GenAI easily? Do you "load balance"
| your usage across other providers for redundancy or cost savings?
| What would happen if there was ever some kind of spot market for
| LLMs?
| crowcroft wrote:
| Simple unstructured to structured data transformation.
|
| I find Flash and Flash Lite are more consistent than others as
| well as being really fast and cheap.
|
| I could swap to other providers fairly easily, but don't intend
| to at this point. I don't operate at a large scale.
| willidiots wrote:
| Low-latency LLM for my home automation. Anecdotally, Gemini was
| much quicker than OpenAI in responding to simple commands.
|
| In general, when I need "cheap and fast" I choose Gemini.
| thimabi wrote:
| In my experience, Gemini 2.5 Pro really shines in some non-
| coding use cases such as translation and summarization via
| Canvas. The gigantic context window and large usage limits help
| in this regard.
|
| I also believe Gemini is much better than ChatGPT in generating
| deep research reports. Google has an edge in web search and it
| shows. Gemini's reports draw on a vast number of sources, thus
| tend to be more accurate. In general, I even prefer its writing
| style, and I like the possibility of exporting reports to
| Google Docs.
|
| One thing that I don't like about Gemini is its UI, which is
| miles behind the competition. Custom instructions, projects,
| temporary chats... these things either have no equivalent in
| Gemini or are underdeveloped.
| hnuser123456 wrote:
| If you're a power user, you should probably be using Gemini
| through AI studio rather than the "basic user" version. That
| allows you to set system instructions, temperature,
| structured output, etc. There's also NotebookLM. Google seems
| to be trying to make a bunch of side projects based on Gemini
| and seeing what sticks, and the generic gemini app/webchat is
| just one of those.
| thimabi wrote:
| My complaint is that any data within AI Studio can be kept
| by Google and used for training purposes -- even if using
| the paid tier of the API, as far as I know. Because of
| that, I end up only using it rarely, when I don't care
| about the fate of the data.
| happyopossum wrote:
| This is only true for the free tier. Paid Ai Studio users
| have strong privacy protections.
| thimabi wrote:
| Thank you for clarifying that. I've researched this once
| again and confirmed that Google treats all AI Studio
| usage as private if there's at least one API project with
| billing enabled in an account.
| VeejayRampay wrote:
| for translation you'll still be limited for longer texts by
| the 65K output limit though I suppose?
| thimabi wrote:
| Yes. I haven't had problems with the output limit so far,
| as I do translations iteratively, over each section of
| longer texts.
|
| What I like the most about translating with Gemini is that
| its default performance is already good enough, and it can
| be improved via the one million tokens of the context
| window. I load to the context my private databases of
| idiomatic translations, separated by language pairs and
| subject areas. After doing that, the need for manually
| reviewing Gemini translations is greatly diminished.
| HDThoreaun wrote:
| I tried swapping for my project which involves having the LLM
| summarize and critique medical research and didn't have great
| results. The prompt I found works best with the main LLM I use
| fucks up the intended format when fed to other LLMs. Thinking
| about refining prompts for each different llm but haven't
| gotten there.
|
| My favorite personal use of Gemini right now is basically as a
| book club. Of course it's not as good as my real one but I
| often can't them to read the books I want and Gemini is always
| ready when I want to explore themes. It's often more profound
| than the book club too and seems a bit less likely to tunnel
| vision. Before LLMs I found exploring book themes pretty
| tedious, often I would have to wait a while to find someone who
| had read it but now I can get into it as soon as I'm done
| reading.
| ttul wrote:
| I can throw a pile of NDAs at it and it neatly pulls out
| relevant stuff from them within a few seconds. The huge context
| window and excellent needle in a haystack performance is great
| for this kind of task.
| spmurrayzzz wrote:
| The NIAH performance is a misleading indicator for
| performance on the tasks people really want the long context
| for. It's great as a smoke/regression test. If you're bad on
| NIAH, you're not gonna do well on the more holistic evals.
|
| But the long context eval they used (MRCR) is limited. It's
| multi-needle, so that's a start, but its not evaluating long
| range dependency resolution nor topic modeling, which are the
| things you actually care about beyond raw retrieval for
| downstream tasks. Better than nothing, but not great for just
| throwing a pile of text at it and hoping for the best.
| Particularly for out-of-distribution token sequences.
|
| I do give google some credit though, they didn't try to hide
| how poorly they did on that eval. But there's a reason you
| don't see them adding RULER, HELMET, or LongProc to this. The
| performance is abysmal after ~32k.
|
| EDIT: I still love using 2.5 Pro for a ton of different
| tasks. I just tend to have all my custom agents compress the
| context aggressively for any long context or long horizon
| tasks.
| NitpickLawyer wrote:
| > The performance is abysmal after ~32k.
|
| Huh. We've not seen this in real-world use. 2.5 pro has
| been the only model where you can throw a bunch of docs
| into it, give it a "template" document (report, proposal,
| etc), even some other-project-example stuff, and tell it to
| gather all relevant context from each file and produce
| "template", and it does surprisingly well. Couldn't
| reproduce this with any other top tier model, at this level
| of quality.
| spmurrayzzz wrote:
| We're a G-suite shop so I set aside a ton of time trying
| to get 2.5 pro to work for us. I'm not entirely unhappy
| with it, its a highly capable model, but the long context
| implosion significantly limits it for the majority of
| task domains.
|
| We have long context evals using internal data that are
| leveraged for this (modeled after longproc specifically)
| and the performance across the board is pretty bad. Task-
| wise for us, it's about as real world as it gets, using
| production data. Summarization, Q&A, coding, reasoning,
| etc.
|
| But I think this is where the in-distribution vs out-of-
| distribution distinction really carries weight. If the
| model has seen more instances of your token sequences in
| training and thus has more stable semantic
| representations of them in latent space, it would make
| sense that it would perform better on average.
|
| In my case, the public evals align very closely with
| performance on internal enterprise data. They both tank
| pretty hard. Notably, this is true for all models after a
| certain context cliff. The flagship frontier models
| predictably do the best.
| jasoncartwright wrote:
| Web scraping - creating semi-structured data from a wide
| variety of horrific HTML soups.
|
| Absolutely do swap out models sometimes, but Gemini 2.0 Flash
| is the right price/performance mix for me right now. Will test
| Gemini 2.5 Flash-Lite tomorrow though.
| k8sToGo wrote:
| I use Gemini 2.5 Flash (non thinking) as a thought partner. It
| helps me organize my thoughts or maybe even give some new input
| I didn't think of before.
|
| I really like to use it also for self reflection where I just
| input my thoughts and maybe concerns and just see what it has
| to say.
| fastest963 wrote:
| Yes, we implemented a separate service internally that
| interfaces with an LLM and so the callers can be agnostic as to
| what provider or model is being used. Haven't needed to load
| balance between models though.
| androng wrote:
| I use it for https://toolong.link Youtube summaries with images
| because only Gemini has easy access to YouTube and it has a
| gigantic context window
| Dnajsre wrote:
| It basically made a university physics exam for me. It almost
| one-shot it as well. Just uploaded some exams from previous
| years together with a latex template and told it to make me a
| similar one. Worked great. Also made it do the solutions.
| jeffbee wrote:
| It's very good at automatically segmenting and recognizing
| handwritten and badly scanned text. I use it to make
| spreadsheets out of handwritten petitions.
| extr wrote:
| Gemini Flash 2.0 is an absolute workhorse of a model at
| extremely low cost. It's obviously not going to measure up to
| frontier models in terms of intelligence but the combination of
| low cost, extreme speed, and highly reliable structured output
| generation make it really pleasant to develop with. I'll
| probably test against 2.5 Lite for an upgrade here.
| wg0 wrote:
| I want to know what use cases you're using if for it it's not
| confidential.
| bradly wrote:
| I've yet to run out of free image gen credits with Gemini, so I
| use it for any low-effort image gen like when my kids want to
| play with it or for testing prompts before committing my o4
| tokens for better quality results.
| sync wrote:
| I use it extensively for https://lexikon.ai - in particular one
| part of what Lexikon does involves processing large amounts of
| images, and the way Google charges for vision is vastly cheaper
| compared to the big alternatives (OpenAI, Anthropic)
| mrtesthah wrote:
| Wow, if I knew that someone was using your product on my
| conversation with them I'd probably have to block them.
| satvikpendem wrote:
| I mean I've copy pasted conversations and emails into
| ChatGPT as well, it often gives good advice on tricky
| problems (essentially like your own personalized
| r/AmITheAsshole chat). This service seems to just automate
| that process.
| upcoming-sesame wrote:
| Turn local real estate agents websites to RSS to get new
| properties on the market before they get uploaded to real
| estate market place platforms.
|
| I give it the HTML, it finds the appropriate selector for the
| property item and then I use a HTML to RSS tool to publish the
| feed
| varun_chopra wrote:
| At one point, when they made Gemini Pro free on AI Studio, Gemini
| was the model of choice for many people, I believe.
|
| Somehow it's gotten worse since then, and I'm back to using
| Claude for serious work.
|
| Gemini is like that guy who keeps talking but has no idea what
| he's actually talking about.
|
| I still use Gemini for brainstorming, though I take its
| suggestions with several grains of salt. It's also useful for
| generating prompts that I can then refine and use with Claude.
| UncleOxidant wrote:
| Used to be able to use Gemini Pro free in cline. Now the API
| limits are so low that you immediately get messages about
| needing to top up your wallet and API queries just don't go
| through. Back to using DeepSeek R1 free in cline (though even
| that eventually stops after a few hours and you have to wait
| until the next day for it to work again). Starting to look like
| I need to setup a local LLM for coding - which means it's time
| to seriously upgrade my PC (well, it's been about 10 years so
| it was getting to be time anyway)
| Workaccount2 wrote:
| By the time you breakeven on whatever you spend on a decent
| LLM capable build, your hardware will be too far behind to
| run whatever is best locally then. It's something that feels
| cheaper but with the pace of things, unless you are churning
| an insane amount of tokens, probably doesn't make sense.
| Never mind that local models running on 24 or 48GB are maybe
| around flash-lite in ability while being slower than SOTA
| models.
|
| Local models are mostly for hobby and privacy, not really
| efficiency.
| FirmwareBurner wrote:
| I found Gemini now terrible for coding. I gave it my code
| blocks and told it what to change and it added tonnes and
| tonnes of needles extra code plus endless comments. It turned a
| tight code into a Papyrus.
|
| ChatGPT is better but tends to be too agreeable, never trying
| to disagree with what you say even if it's stupid so you end up
| shooting yourself in the foot.
|
| Claude seems like the best compromise.
|
| Just my two kopecks.
| unshavedyak wrote:
| Yea, i had similar experiences. At first it felt like it solved
| complex problems really well, but then i realized i was having
| trouble steering it for simple things. It was also very
| verbose.
|
| Overall though my primary concern is the UX, and Claude Code is
| the UX of choice for me currently.
| huevosabio wrote:
| They made it talk like buzzfeed articles for every single
| interaction. It's absolutely horrible
| therealmarv wrote:
| not according to Aider leaderboard
| https://aider.chat/docs/leaderboards/
|
| I use only the APIs directly with Aider (so no experience with
| AI Studio).
|
| My feeling with Claude is that they still perform good with
| weak prompts, the "taste" is maybe a little better when the
| direction is kinda unknown by the prompter.
|
| When the direction is known I see Gemini 2.5 Pro (with
| thinking) on top of Claude with code which does not break. And
| with o4-mini and o3 I see more "smart" thinking (as if there is
| a little bit of brain inside these models) at the expense of
| producing unstable code (Gemini produces more stable code).
|
| I see problems with Claude when complexity increases and I
| would put it behind Gemini and o3 in my personal ranking.
|
| So far I had no reason to go back to Claude since o3-mini was
| released.
| stavros wrote:
| I just spent $35 for Opus to solve a problem with a hardware
| side-project (I'm turning an old rotary phone into a meeting
| handset so I can quit meetings by hanging up, if you must
| know). It didn't solve the problem, it churned and churned
| and spent a ton of money.
|
| I was much more satisfied with o3 and Aider, I haven't tried
| them on this specific problem but I did quite a bit of work
| on the same project with them last night. I think I'm being a
| bit unfair, because what Claude got stuck on seems to be a
| hard problem, but I don't like how they'll happily consume
| all my money trying the same things over and over, and never
| say "yeah I give up".
| alecco wrote:
| Give them feedback.
| stavros wrote:
| Feedback on what?
| CamperBob2 wrote:
| When I obtain results from one paid model that are
| significantly better than what I previously got from
| another paid model, I'll typically give a thumbs-down to
| the latter and point out in the comment that it was
| beaten by a competitor. Can't hurt.
| stavros wrote:
| Ah, this wasn't from the web interface, I was using
| Claude Code. I don't think it has a feedback mechanism.
| antgiant wrote:
| For basically that same price you could get one of these
| :-)
|
| https://www.amazon.com/Cell2jack-Cellphone-Adapter-
| Receive-l...
| stavros wrote:
| Where's the fun in that?!
| sans_souse wrote:
| wait, you're using a _rotary phone_ ?
| stavros wrote:
| I want to!
| macNchz wrote:
| Using all of the popular coding models pretty extensively
| over the past year, I've been having great success with
| Gemini 2.5 Pro as far as getting working code the first time,
| instruction following around architectural decisions, and
| staying on-task. I use Aider and write mostly Python, JS, and
| shell scripts. I've spent hundreds of dollars on the Claude
| API over time but have switched almost entirely to Gemini.
| The API itself is also much more reliable.
|
| My only complaint about 2.5 Pro is around the inane comments
| it leaves in the code (// Deleted varName here).
| ZeWaka wrote:
| If you use one of the AI static instructions methods (e.g.,
| .github/copilot-instructions.md) and tell it to not leave
| the useless comments, that seems to solve the issue.
| macNchz wrote:
| I've been intending to try some side by side tests with
| and without a conventions file instructing it not to
| leave stupid comments--I'm curious to see if somehow
| they're providing value to the model, e.g. in multi-turn
| edits.
| luckydata wrote:
| it's easier to just make it do a code review with focus
| on removing unhelpful comments instead of asking it not
| to do it the first time. I do the cleanup after major
| rounds of work and that strategy seems to work best for
| me.
| jjani wrote:
| This was not my experience with the earlier preview (03),
| where its insistence on comment spam was too strong to
| overcome. Wonder if this adherence improved in the 05 or
| 06 updates.
| sans_souse wrote:
| can you elaborate on this?
| avereveard wrote:
| I'm using pro for backend and claude for ux work, claude is
| so much thoughtful about how user interact with software
| and can usually replicate better the mock up that gpt4o
| image generator produces, while not being overly fixated on
| the mockup design itself.
|
| My complaint is that it catches python exceptions and don't
| log them by default.
| hirako2000 wrote:
| You feelings of a little brain in there, and stable code are
| unfounded. All these models collapse pretty fast. If not due
| to context limit, then in their inability to interpret
| problems.
|
| An LLM is just statistical regressions with a llztjora of
| engineering tricks, mostly NLP to produce an illusion.
|
| I don't mean it's useless. I mean comparing these ever
| evolving models is like comparing escort staff in NYC vs
| those in L.A, hard to reach any conclusjon. We are getting
| fooled.
|
| On the price increase, it seems Google was aggressively
| looking for adoption, Gemini was for a short range of time
| the best value for money of all the LLMs out there. Adoption
| likely surged, scaling needs be astronomical, costing Google
| billions to keep up. The price adjustment could've been
| expected before they announced it.
| willseth wrote:
| Same experience here. I even built a Gem with am elaborate
| prompt instructing it how to be concise, but it still gives
| annoying long-winded responses and frequently expands the scope
| of its answer far beyond the prompt.
| theturtletalks wrote:
| I feel like this is part of the AI playbook now. Launch a
| really strong, capable model (expensive price inference) and
| once users think it's SOTA, neuter it so the cost is cheaper
| and most users won't notice.
|
| The same happened with GPT-3.5. It was so good early on and
| got worse as OpenAI began to cut costs. I feel like when
| GPT-4.1 was cloaked as Optimus on Openrouter, it was really
| good, but once it launched, it also got worse.
| carlos22 wrote:
| That is the capitalism' playbook all along. Its just much
| faster because its just software. But they do it for
| everything all the time.
| andybak wrote:
| Do you mind explaining how you see this working as a
| nefarious plot? I don't see an upside in this case so I'm
| going with the old "never ascribe to malice" etc
| theturtletalks wrote:
| I disagree with the comparison between LLM behavior and
| traditional software getting worse. When regular software
| declines in quality, it's usually noticeable through UI
| changes, release notes, or other signals. Companies often
| don't bother hiding it, since their users are typically
| locked into their ecosystem.
|
| LLMs, on the other hand, operate under different
| incentives. It's in a company's best interest to
| initially release the strongest model, top the
| benchmarks, and then quietly degrade performance over
| time. Unlike traditional software, LLMs have low
| switching costs, users can easily jump to a better
| alternative. That makes it more tempting for companies to
| conceal model downgrades to prevent user churn.
| jjani wrote:
| > When regular software declines in quality, it's usually
| noticeable through UI changes, release notes, or other
| signals.
|
| Counterexample: 99% of average Joes have no idea how
| incredibly enshittified Google Maps has become, to just
| name one app. These companies intentionally boil the frog
| very slowly, and most people are incredibly bad at
| noticing gradual changes (see global warming).
|
| Sure, they could know by comparing, but you could also
| know whether models are changing behind the scenes by
| having sets of evals.
| theturtletalks wrote:
| This is where switching costs matter. Take Google Maps,
| many people can't switch to another app. In some areas,
| it's the only app with accurate data, so Google can
| degrade the experience without losing users.
|
| We can tell it's getting worse because of UI changes,
| slower load times, and more ads. The signs are visible.
|
| With LLMs, it's different. There are no clear cues when
| quality drops. If responses seem off, users often blame
| their own prompts. That makes it easier for companies to
| quietly lower performance.
|
| That said, many of us on HN use LLMs mainly for coding,
| so we can tell when things get worse.
|
| Both cases involve the "boiling frog" effect, but with
| LLMs, users can easily jump to another pot. With
| traditional software, switching is much harder.
| dr_kiszonka wrote:
| They nerfed Pro 2.5 significantly in the last few months. Early
| this year, I had genuinely insightful conversations with Gemini
| 2.5 Pro. Now they are mostly frustrating.
|
| I also have a personal conspiracy theory, i.e., that once a
| user exceeds a certain use threshold of 2.5 Pro in the Google
| Gemini app, they start serving a quantized version. Of course,
| I have no proof, but it certainly feels that way.
| esafak wrote:
| I wonder how smart they are about quantizing. Do they look at
| feedback to decide which users won't mind?
| conradkay wrote:
| Maybe they've been focusing so much on improving coding
| performance with RL for the new versions/previews that other
| areas degraded in performance
| dr_kiszonka wrote:
| I think you are right and this is probably the case.
|
| Although, given that I rapidly went from +4 to 0 karma, a
| few other comments in this topic are grey, and at least one
| is missing, I am getting suspicious. (Or maybe it is just
| lunch time in MTV.)
| chrismustcode wrote:
| When I ask it do to do something in cursor it goes full
| sherlock thinking about every possible outcome.
|
| Just claude 4 sonnet with thinking just has a bit think then
| does it
| jasonjmcghee wrote:
| I have no inside information but feels like they quantized it.
| I've seen patterns that I usually only see in quantized models
| like getting stuck repeating a single character indefinitely
| noisy_boy wrote:
| They should just roll back to the preview versions. Those were
| so much more even keeled and actually did some useful pushback
| instead of this cheerleader-on-steroids version they GA'd.
| k8sToGo wrote:
| But they claim it's the same model and version?
| jbellis wrote:
| Love to see it, this takes Flash Lite from "don't bother"
| territory for writing code to potentially useful. (Besides being
| inexpensive, Flash Lite is _fast_ -- almost always sub-second, to
| as low as 200ms. Median around 400ms IME.)
|
| Brokk (https://brokk.ai/) currently uses Flash 2.0 (non-Lite) for
| Quick Edits, we'll evaluate 2.5 Lite now.
|
| ETA: I don't have a use case for a thinking model that is dumber
| than Flash 2.5, since thinking negates the big speed advantage of
| small models. Curious what other people use that for.
| hs86 wrote:
| I am always disappointed when I compare the answers to the same
| queries on 2.5 Pro vs. o4-mini/o3. But trying out the same query
| in AI Studio gives much better results, closer to OpenAI's
| models. What is wrong with 2.5 Pro in the Gemini app? I can't
| believe that the model in their consumer app would produce the
| same benchmark results as 2.5 Pro in the API or AI Studio.
| mh- wrote:
| I don't have any inside information, but I'm sure there are
| different system prompts used in the Gemini chat interface vs
| the API. On OpenAI/ChatGPT they're sometimes dramatically
| different.
| thimabi wrote:
| The models in the Gemini app are nerfed in comparison to those
| in AI Studio: they have less thinking budget, output less
| tokens, and have various safety filters. There's certainly a
| trade-off between using AI Studio for its better performance
| and using the API or the Gemini app in a way that doesn't
| involve Google keeping your data for training purposes.
| 2Gkashmiri wrote:
| I have a huge background.js file from a now removed browser
| extension that the Devs made into a single line. Around 800KB of
| a single line file I think....
|
| I tried many free stuff to try to refactor it but they all loose
| context window quickly.
| mh- wrote:
| There are myriad non-LM tools that can deobfuscate and prettify
| JS. I used them with success long before LLMs were en vogue.
| BonoboIO wrote:
| Which extension is it?
| sergiotapia wrote:
| Considering moving from Groq Llama 3.3 70b to Gemini 2.5 Flash
| Lite for one of my use cases. Results are coming in great, and
| it's very fast (important for my real-time user perception
| needs).
|
| What kind of rate limits do these new Gemini models have?
| UncleOxidant wrote:
| Are you using Groq Llama 3.3 70b from something like cline? Is
| it free and what are the API query limits?
| sergiotapia wrote:
| I'm using it from their HTTP API. Limits I can't remember
| what they were initially tbh, I had to reach out through
| backchannels to get it increased to 300,000 tokens per
| minute.
| serjester wrote:
| I'm glad that they standardized pricing for the thinking vs non-
| thinking variant. A couple weeks ago I accidentally spent
| thousands of extra dollars by forgetting to set the thinking
| budget to zero. Forgetting a single config parameter should not
| automatically raise the model cost 5X.
|
| [edit] I'm less excited about this because it looks like their
| solution was to dramatically raise the base price on the non-
| thinking variant.
| heliophobicdude wrote:
| Wishing they release the Gemini Diffusion model. It'll quickly
| replace the default model for Aider.
| causal wrote:
| Why do you think so? I've played with the Diffusion model a bit
| and it makes a lot of mistakes
| vessenes wrote:
| It feels to me like properly instrumented, these diffusion
| models are going to be really powerful coding tools. Imagine a
| "smart" model carving out a certain number of tokens in a
| response for each category of response output, then diffusing
| the categories.
| GaggiX wrote:
| 2.5 Flash Lite seems better at everything compare to 2.0 Flash
| Lite with the only exception being SimpleQA, so there is probably
| a small tradeoff on pop culture knowledge for coding, math,
| science, reasoning and multimodal tasks.
| simonw wrote:
| They don't mention it in the post, but it looks like this
| includes a price increase for the Gemini 2.5 Flash model.
|
| For 2.5 Flash Preview
| https://web.archive.org/web/20250616024644/https://ai.google...
|
| $0.15/million input text / image / video
|
| $1.00/million audio
|
| Output: $0.60/million non-thinking, $3.50/million thinking
|
| The new prices for Gemini 2.5 Flash ditch the difference between
| thinking and non-thinking and are now:
| https://ai.google.dev/gemini-api/docs/pricing
|
| $0.30/million input text / image / video (2x more)
|
| $1.00/million audio (same)
|
| $2.50/million output - significantly more than the old non-
| thinking price, less than the old thinking price.
| rudedogg wrote:
| A cool 2x+ price increase.
|
| And Gemini 2.0 Flash was $0.10/$0.40.
| jjani wrote:
| 4x price increase over preview output for non-thinking.
| __jl__ wrote:
| 1.5 -> 2.0 was a price increase as well (double, I think, and
| something like 4x for image input)
|
| Now 2.0 -> 2.5 is another hefty price increase.
| k8sToGo wrote:
| You can also see this difference in open router.
|
| But why is there only thinking flash now?
| hnuser123456 wrote:
| Apparently, you can make a request to 2.5 flash to not use
| thinking, but it will still sometimes do it anyways, this has
| been an issue for months, and hasn't been fixed by model
| updates: https://github.com/google-gemini/cookbook/issues/722
| Tiberium wrote:
| It might be a bit confusing, but there's no "only thinking
| flash" - it's a single model, and you can turn off thinking
| if you set thinking budget to 0 in the API request.
| Previously 2.5 Flash Preview was much cheaper with the
| thinking budget set to 0, now the price is the same. Of
| course, with thinking enabled the model will still use far
| more output tokens than the non-thinking mode.
| irthomasthomas wrote:
| "Soon, AI too cheap to meter" "Meantime, price go up".
| tekno45 wrote:
| "will be too cheap to meter" means we're definitely metering
| it now.
| skybrian wrote:
| There are a lot more price drops, though.
| nicce wrote:
| We have likely seen the cheapest prices already. Once we
| can't function without them anymore - go as high as you can!
| nico wrote:
| Hopefully we get more competition and someone willing to
| undercut the more expensive options
| nicce wrote:
| Entering the market and being competitive gets more
| difficult all the time. People want the best and fastest
| models - can you compete with trillion dollar
| datacenters?
| overfeed wrote:
| It's more likely the shareholder zeitgeist will soon
| shift to demanding returns on the ungodly amounts already
| invested into AI.
| hirako2000 wrote:
| By then comparable or even better models will easily run on
| edge.
|
| So if they crank up the prices we could just switch to
| local and not get lured by bigger and bigger models, rag,
| Agentic, MCP driven tech as if all of that couldn't run
| locally either.
| gnatolf wrote:
| I am not as optimistic that locally run models will be
| able to compete anytime soon. And even if, the price to
| run them means you have to buy the compute/gear for a
| price that is likely equivalent to a lot of 'remote'
| tokens
| nicce wrote:
| The most meaningful models will run in the future on
| those trillion dollar data centers that are currently
| being build.
| llm_nerd wrote:
| Not too long ago Google was a bit of a joke in AI and their
| offerings were uncompetitive. For a while a lot of their
| preview/beta models had a price of 0.00. They were literally
| giving it away for free to try to get people to consider
| their offerings when building solutions.
|
| As they've become legitimately competitive they have moved
| towards the pricing of their competitors.
| tom_m wrote:
| No way. AI pricing is going up because people are willing to
| pay for it.
| victorbjorklund wrote:
| Just google. They were behind. So they just dumped their
| prices to get a foot in the door. Now they are popular and
| can raise it to market prices.
| sodality2 wrote:
| I still don't think there's any real stickiness to using a
| Google model over any other model, with things like
| openrouter. So maybe for brand recognition alone.
| Workaccount2 wrote:
| The blog post has more info about the pricing changes
|
| https://developers.googleblog.com/en/gemini-2-5-thinking-mod...
| jjani wrote:
| The real news is that non-thinking output is now 4x more
| expensive, which they of course carefully avoid mentioning in
| the blog, only comparing the thinking prices.
|
| How cute they are with their phrasing:
|
| > $2.50 / 1M output tokens (*down from $3.50 output)
|
| Which should be "up from $0.60 (non-thinking)/down from $3.50
| (thinking)"
| amazingamazing wrote:
| Is it possible to get non-thinking only now, though? If
| not, why would that matter, since it's irrelevant?
| jjani wrote:
| Yes, by setting the thinking budget to 0. Which is very
| common when a task doesn't need thinking.
|
| In addition, it's also relevant because for the last 3
| months people have built things on top of this.
| amazingamazing wrote:
| interesting - why wouldn't you use dynamic thinking? and
| yeah, sucks when the price changes.
| dcre wrote:
| It makes responses much slower with zero benefit for many
| tasks. Flash with thinking off is very fast.
| Workaccount2 wrote:
| To be fair, the point of preview models and stable
| releases is so you know what is stable to build on.
| drag0s wrote:
| one example where non-thinking matters would be latency-
| sensitive workflows, for example voice AI.
| drift_code wrote:
| They seem just rebrand the non-thinking model to flash-
| lite, so it's less expensive than before
| jjani wrote:
| Not at all. Non-thinking flash is... flash with the
| thinking budget set to 0 (which you can still run that
| way, just at 2x input 4x output pricing). Flash-lite is
| far weaker, unusable for the overwhelming majority of
| usecases of flash. A quick glance at the benchmark
| reveals this.
| rvnx wrote:
| Yeah, so basically their announcement is "good news, we
| tripled the price, and will deprecate Gemini Flash 2.0
| asap"
| mcintyre1994 wrote:
| The OP says Flash-Lite has thinking and non-thinking, so
| it's not that simple.
| shock wrote:
| Do you work for google?
| pama wrote:
| "While we strive to maintain consistent pricing between
| preview and stable releases to minimize disruption, this is a
| specific adjustment reflecting Flash's exceptional value,
| still offering the best cost-per-intelligence available."
| dangoodmanUT wrote:
| Good catch, that's a pretty notable change considering this was
| about to be the GOAT of audio-to-audio
| zelias wrote:
| Not sure where else to post this, but when attempting to use any
| of the Gemini 2.5 models via API, I receive an "empty content"
| response about 50% of the time. To be clear, the API responds
| successfully, but the `content` returned by the LLM is just an
| empty string.
|
| Has anyone here had any luck working around this problem?
| Tiberium wrote:
| What finish reason are you getting? Perhaps your code sets a
| low max_tokens, so the generation stops while the model is
| still thinking, without giving any actual output.
| zelias wrote:
| The finish reason is `length`. I have tried setting minimal
| token budgets, really small prompts, and max lengths of
| various sizes from 100-4000 and nothing seems to make a
| consistent dent in the behavioral pattern.
| zzleeper wrote:
| Good luck using 2.5 for anything non-trivial.
|
| I have about 500,000 news articles I am parsing. OpenAI models
| work well but found Gemini had fewer mistakes.
|
| Problem is; they give me a terrible 10k RPD limit. To increase to
| the next tier, they then require a minimum amount of spending but
| I can't reach that amount even when maxing the RPD limit for
| multiple days in a row.
|
| I emailed them twice and completed their forms but everyone knows
| how this works. So now I'm back at OpenAI, with a model with a
| bit more mistakes but that won't 403 me after half an hour of
| using it due to their limits.
| eldenring wrote:
| I'm guessing now that it is GA this won't be a problem.
| zzleeper wrote:
| I wish! The tier-based limits are still the same!
|
| At least it's more expensive now so I guess I will be able to
| hop to the next tier sooner? -\\_(tsu)_/-
| be7a wrote:
| The rate limits apply only to the Gemini API. There is also
| Vertex from GCP, which offers the same models (and even more,
| such as Claude) at the same pricing, but with much higher rate
| limits (basically none, as long as they don't need to cut
| anyone off with provisioned throughput iiuc) and with a process
| to get guaranteed throughput.
| b0a04gl wrote:
| been testing gemini flash lite. latency is good, responses land
| under 400ms most times. useful for low-effort rewrites or
| boilerplate filler. quality isn't stable though : context drifts
| after 4-5 turns, especially with anything recursive or
| structured. tried tagging it into prompt chains but fallback
| logic ends up too aggressive. good for assist, not for logic,
| wouldn't anchor anything serious on it yet
| lvl155 wrote:
| I am very impressed with Gemini and stopped using OpenAI.
| Sometimes, I ping all three major models on OpenRouter but 90% is
| on Gemini now. Compare that to 90% ChatGPT last year.
| aatd86 wrote:
| Same. For now I have canceled my claude subscription. Gemini
| has been catching up.
| glohbalrob wrote:
| Also me. Still pay for OpenAI, I use gpt4 for excel work and
| is super fast and able to do more excel related work like
| combine files that come up often for projects I work on.
| codingwagie wrote:
| I love to hate on google, but yeah their models are really
| good. The larger context window is huge
| kapildev wrote:
| Doesn't OpenAI's GPT 4.1 also have 1 million context length?
| tiahura wrote:
| Gemini 2.5 doesn't get enough credit for the quality of its
| writing in non-code (eg law) topics. It's definitely a notch
| below Claude 4, but well ahead of ChatGPT 4o, 4.5, o3.
| jjani wrote:
| Classic bait-and-switch to make developers build things on top
| off models for 2 months, and then raise input price by 2x and
| output by 4x. But hey, it's Google, wouldn't expect anything else
| from an advertising company.
| zurfer wrote:
| for anyone, who was expecting more news: the GA models benchmark
| basically the same as the last preview models. It's really just
| Google telling us that we get less api errors and this model will
| have a checkpoint for a longer time.
| dinesh2609 wrote:
| 6.33X increase in the price of Audio processing compared to 2.0
| Flash-Lite
|
| Gemini 2.5 Flash Lite (Audio Input) - $0.5/million tokens
|
| Gemini 2.0 Flash Lite (Audio Input) - $0.075/million tokens
|
| Wonder what led to such a high bump in Audio token processing
| sethkim wrote:
| I run a batch inference/LLM data processing service and we do a
| lot of work around cost and performance profiling of (open-
| weight) models.
|
| One odd disconnect that still exists in LLM pricing is the fact
| that providers charge linearly with respect to token consumption,
| but costs are actually quadratic with an increase in sequence
| length.
|
| At this point, since a lot of models have converged around the
| same model architecture, inference algorithms, and hardware - the
| chosen costs are likely due to a historical, statistical analysis
| of the shape of customer requests. In other words, I'm not
| surprised to see costs increase as providers gather more data
| about real-world user consumption patterns.
| raybb wrote:
| It's a bummer that 2.5 Pro is still removed from the free tier of
| the API.
| zhyder wrote:
| Blended price (assuming 3:1 for input:output tokens) is 3.24x of
| what was stated before [1], and now nearly 5x of 2.0 Flash. Makes
| 2.0 Flash a still competitive option for many use-cases,
| particularly ones that aren't coding-heavy I think. A slightly
| poorer performing model can net perform better through multiple
| prompt passes. Bummer, was hoping 2.5 Flash would be a slam dunk
| choice.
|
| [1] -
| https://web.archive.org/web/20250616024644/https://ai.google...
| nikanj wrote:
| I need an AI model to be able to keep track of the AI model
| names.
| andrewstuart wrote:
| Gemini strangely says you cannot upload all sorts of file types.
|
| But it accepts them just fine if you upload a zip file.......
| which you can only do in AI studio.
| andrewstuart wrote:
| I really wish all the AI companies would down tools on all
| development until they work out file downloads, ftp, sftp, git
| ANY way to access the files other than copy paste and "download
| file".
|
| The workflow is crushingly tedious.
|
| And no I don't want to use an AI IDE or some other tool. I like
| the UI of Gemini chat and AI Studio and I want them improved.
| simonw wrote:
| I tried using the three new models to transcribe the audio of
| this morning's Gemini Twitter Space.
|
| I got very strong results from 2.5 Pro and 2.5 Flash, but 2.5
| Flash Lite sadly got stuck in a loop until it ran out of output
| tokens:
|
| _Um, like, what did the cows bring to you? Nothing. And then,
| um, and then, uh, and then, uh, and then, uh, and then, uh, and
| then, uh, and then, uh, and then, uh, and..._
|
| Notes on my results (including the transcripts which worked,
| which included timestamps and guessed speaker names) here:
| https://simonwillison.net/2025/Jun/17/gemini-2-5/#transcribi...
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