▲Don’t let the “flash” name fool you, this is an amazing model.
I have been playing with it for the past few weeks, it’s genuinely my new favorite; it’s so fast and it has such a vast world knowledge that it’s more performant than Claude Opus 4.5 or GPT 5.2 extra high, for a fraction (basically order of magnitude less!!) of the inference time and price
thecupisblue3 hours ago
[-] Oh wow - I recently tried 3 Pro preview and it was too slow for me.
After reading your comment I ran my product benchmark against 2.5 flash, 2.5 pro and 3.0 flash.
The results are better AND the response times have stayed the same.
What an insane gain - especially considering the price compared to 2.5 Pro.
I'm about to get much better results for 1/3rd of the price. Not sure what magic Google did here, but would love to hear a more technical deep dive comparing what they do different in Pro and Flash models to achieve such a performance.
Also wondering, how did you get early access? I'm using the Gemini API quite a lot and have a quite nice internal benchmark suite for it, so would love to toy with the new ones as they come out.
Alright so we have more benchmarks including hallucinations and flash doesn't do well with that, though generally it beats gemini 3 pro and GPT 5.1 thinking and gpt 5.2 thinking xhigh (but then, sonnet, grok, opus, gemini and 5.1 beat 5.2 xhigh) - everything. Crazy.
https://artificialanalysis.ai/evaluations/omniscience
giancarlostoro51 minutes ago
[-] I wonder at what point will everyone who over-invested in OpenAI will regret their decision (expect maybe Nvidia?). Maybe Microsoft doesn't need to care, they get to sell their models via Azure.
reply▲Thanks, having it walk a hardcore SDR signal chain right now --- oh damn it just finished. The blog post makes it clear this isn't just some 'lite' model - you get low latency and cognitive performance. really appreciate you amplifying that.
reply▲What are you using it for and what were you using before?
reply▲tonyhart751 minutes ago
[-] I think google is the only one that still produce general knowledge LLM right now
claude is coding model from the start but GPT is in more and more becoming coding model
Imustaskforhelp37 minutes ago
[-] I agree with this observation. Gemini does feel like code-red for basically every AI company like chatgpt,claude etc. too in my opinion if the underlying model is both fast and cheap and good enough
I hope open source AI models catch up to gemini 3 / gemini 3 flash. Or google open sources it but lets be honest that google isnt open sourcing gemini 3 flash and I guess the best bet mostly nowadays in open source is probably glm or deepseek terminus or maybe qwen/kimi too.
unsupp0rted2 hours ago
[-] How good is it for coding, relative to recent frontier models like GPT 5.x, Sonnet 4.x, etc?
reply▲Can you be more specific on the tasks you’ve found exceptional ?
reply▲Gemini 2.0 flash was good already for some tasks of mine long time ago..
reply▲Cool! I've been using 2.5 flash and it is pretty bad. 1 out of 5 answers it gives will be a lie. Hopefully 3 is better
reply▲Did you try with the grounding tool? Turning it on solved this problem for me.
reply▲what if the lie is a logical deduction error not a fact retrieval error
reply▲The error rate would still be improved overall and might make it a viable tool for the price depending on the usecase.
reply▲How did you get early access?
reply▲Just to point this out: many of these frontier models cost isn't that far away from
two orders of magnitude more than what DeepSeek charges. It doesn't compare the same, no, but with coaxing I find it to be a pretty capable competent coding model & capable of answering a lot of general queries pretty satisfactorily (but if it's a short session, why economize?). $0.28/m in, $0.42/m out. Opus 4.5 is $5/$25 (17x/60x).
I've been playing around with other models recently (Kimi, GPT Codex, Qwen, others) to try to better appreciate the difference. I knew there was a big price difference, but watching myself feeding dollars into the machine rather than nickles has also founded in me quite the reverse appreciation too.
I only assume "if you're not getting charged, you are the product" has to be somewhat in play here. But when working on open source code, I don't mind.
happyopossum2 hours ago
[-] Two orders of magnitude would imply that these models cost $28/m in and $42/m out. Nothing is even close to that.
reply▲jauntywundrkind54 minutes ago
[-] To me as an engineer, 60x for output (which is most of the cost I see, AFAICT) is not
that significantly different from 100x.
I tried to be quite clear with showing my work here. I agree that 17x is much closer to a single order of magnitude than two. But 60x is, to me, a bulk enough of the way to 100x that yeah I don't feel bad saying it's nearly two orders (it's 1.78 orders of magnitude). To me, your complaint feels rigid & ungenerous.
My post is showing to me as -1, but I standby it right now. Arguing over the technicalities here (is 1.78 close enough to 2 orders to count) feels besides the point to me: DeepSeek is vastly more affordable than nearly everything else, putting even Gemini 3 Flash here to shame. And I don't think people are aware of that.
I guess for my own reference, since I didn't do it the first time: at $0.50/$3.00 / M-i/o, Gemini 3 Flash here is 1.8x & 7.1x (1e1.86) more expensive than DeepSeek.
Feels like Google is really pulling ahead of the pack here. A model that is cheap, fast and good, combined with Android and gsuite integration seems like such powerful combination.
Presumably a big motivation for them is to be first to get something good and cheap enough they can serve to every Android device, ahead of whatever the OpenAI/Jony Ive hardware project will be, and way ahead of Apple Intelligence. Speaking for myself, I would pay quite a lot for truly 'AI first' phone that actually worked.
This is awesome. No preview release either, which is great to production.
They are pushing the prices higher with each release though:
API pricing is up to $0.5/M for input and $3/M for output
For comparison:
Gemini 3.0 Flash: $0.50/M for input and $3.00/M for output
Gemini 2.5 Flash: $0.30/M for input and $2.50/M for output
Gemini 2.0 Flash: $0.15/M for input and $0.60/M for output
Gemini 1.5 Flash: $0.075/M for input and $0.30/M for output (after price drop)
Gemini 3.0 Pro: $2.00/M for input and $12/M for output
Gemini 2.5 Pro: $1.25/M for input and $10/M for output
Gemini 1.5 Pro: $1.25/M for input and $5/M for output
I think image input pricing went up even more.
Correction: It is a preview model...
Thanks that was a great breakup of cost. I just assumed before that it was the same pricing. The pricing probably comes from the confidence and the buzz around Gemini 3.0 as one of the best performing models. But competetion is hot in the area and it's not too far where we get similar performing models for cheaper price.
reply▲mips_avatar3 hours ago
[-] I'm more curious how Gemini 3 flash lite performs/is priced when it comes out. Because it may be that for most non coding tasks the distinction isn't between pro and flash but between flash and flash lite.
reply▲This is a preview release.
reply▲YetAnotherNick2 hours ago
[-] For comparison, GPT-5 mini is $0.25/M for input and $2.00/M for output, so double the price for input and 50% higher for output.
reply▲flash is closer to sonnet than gpt minis though
reply▲Are these the current prices or the prices at the time the models were released?
reply▲Mostly at the time of release except for 1.5 Flash which got a price drop in Aug 2024.
Google has been discontinuing older models after several months of transition period so I would expect the same for the 2.5 models. But that process only starts when the release version of 3 models is out (pro and flash are in preview right now).
The price increase sucks, but you really do get a whole lot more. They also had the "Flash Lite" series, 2.5 Flash Lite is 0.10/M, hopefully we see something like 3.0 Flash Lite for .20-.25.
reply▲is there a website where i can compare openai, anthropic and gemini models on cost/token ?
reply▲There are plenty. But it's not the comparison you want to be making. There is too much variability between the number of tokens used for a single response, especially once reasoning models became a thing. And it gets even worse when you put the models into a variable length output loop.
You really need to look at the cost per task. artificialanalysis.ai has a good composite score, measures the cost of running all the benchmarks, and has 2d a intelligence vs. cost graph.
These flash models keep getting more expensive with every release.
Is there an OSS model that's better than 2.0 flash with similar pricing, speed and a 1m context window?
Edit: this is not the typical flash model, it's actually an insane value if the benchmarks match real world usage.
> Gemini 3 Flash achieves a score of 78%, outperforming not only the 2.5 series, but also Gemini 3 Pro. It strikes an ideal balance for agentic coding, production-ready systems and responsive interactive applications.
The replacement for old flash models will be probably the 3.0 flash lite then.
thecupisblue3 hours ago
[-] Yes, but the 3.0 Flash is cheaper, faster and better than 2.5 Pro.
So if 2.5 Pro was good for your usecase, you just got a better model for about 1/3rd of the price, but might hurt the wallet a bit more if you use 2.5 Flash currently and want an upgrade - which is fair tbh.
I think it's good, they're raising the size (and price) of flash a bit and trying to position Flash as an actually useful coding / reasoning model. There's always lite for people who want dirt cheap prices and don't care about quality at all.
reply▲mips_avatar2 hours ago
[-] For my apps evals Gemini flash and grok 4 fast are the only ones worth using. I'd love for an open weights model to compete in this arena but I haven't found one.
reply▲fullstackwife4 hours ago
[-] cost of e2e task resolution should be cheaper, even if single inference cost is higher, you need fewer loops to solve a problem now
reply▲Sure, but for simple tasks that require a large context window, aka the typical usecase for 2.0 flash, it's still significantly more expensive.
reply▲simonsarris4 hours ago
[-] Even before this release the tools (for me: Claude Code and Gemini for other stuff) reached a "good enough" plateau that means any other company is going to have a hard time making me (I think soon most users) want to switch. Unless a new release from a different company has a real paradigm shift, they're simply sufficient. This was not true in 2023/2024 IMO.
With this release the "good enough" and "cheap enough" intersect so hard that I wonder if this is an existential threat to those other companies.
Why wouldn't you switch? The cost to switch is near zero for me. Some tools have built in model selectors. Direct CLI/IDE plug-ins practically the same UI.
reply▲I think a big part of the switching cost is the cost of learning a different model's nuances. Having good intuition for what works/doesn't, how to write effective prompts, etc.
Maybe someday future models will all behave similarly given the same prompt, but we're not quite there yet
Not OP, but I feel the same way. Cost is just one of the factor. I'm used to Claude Code UX, my CLAUDE.md works well with my workflow too. Unless there's any significant improvement, changing to new models every few months is going to hurt me more.
reply▲I used to think this way. But I moved to AGENTS.md. Now I use the different UI as a mental context separation. Codex is working on Feature A, Gemini on feature B, Claude on Feature C. It has become a feature.
reply▲You're assuming that different models need the same stuff in AGENTS.md
In my experience, to get the best performance out of different models, they need slightly different prompting.
theLiminator4 hours ago
[-] For me, the last wave of models finally started delivering on their agentic coding promises.
reply▲This has been my experience exactly. Even over just the last few weeks I’ve noticed a dramatic drop in having to undo what the agents have done.
reply▲But for me the previous models were routinely wrong time wasters that overall added no speed increase taking the lottery of whether they'd be correct into account.
reply▲Correct. Opus 4.5 'solved' software engineering. What more do I need? Businesses need uncapped intelligence, and that is a very high bar. Individuals often don't.
reply▲If Opus is one-size-fits-all, then why Claude keeps the other series? (rethorical).
Opus and Sonnet are slower than Haiku. For lots of less sophisticated tasks, you benefit from the speed.
All vendors do this. You need smaller models that you can rapid-fire for lots of other reasons than vibe coding.
Personally, I actually use more smaller models than the sophisticated ones. Lots of small automations.
I just can't stop thinking though about the vulnerability of training data
You say good enough. Great, but what if I as a malicious person were to just make a bunch of internet pages containing things that are blatantly wrong, to trick LLMs?
The internet has already tried this, for about a few decades. The garbage is in the corpus; it gets weighted as such
reply▲My main issue with Gemini is that business accounts can't delete individual conversations. You can only enable or disable Gemini, or set a retention period (3 months minimum), but there's no way to delete specific chats. I'm a paying customer, prices keep going up, and yet this very basic feature is still missing.
reply▲It's a cool release, but if someone on the google team reads that:
flash 2.5 is awesome in terms of latency and total response time without reasoning. In quick tests this model seems to be 2x slower. So for certain use cases like quick one-token classification flash 2.5 is still the better model.
Please don't stop optimizing for that!
reply▲reply▲Yes I tried it with minimal and it's roughly 3 seconds for prompts that take flash 2.5 1 second.
On that note it would be nice to get these benchmark numbers based on the different reasoning settings.
Tiberium35 minutes ago
[-] You can still set thinking budget to 0 to completely disable reasoning, or set thinking level to minimal or low.
reply▲That's more of a flash-lite thing now, I believe
reply▲It has a SimpleQA score of 69%, a benchmark that tests knowledge on extremely niche facts, that's actually ridiculously high (Gemini 2.5 *Pro* had 55%) and reflects either training on the test set or some sort of cracked way to pack a ton of parametric knowledge into a Flash Model.
I'm speculating but Google might have figured out some training magic trick to balance out the information storage in model capacity. That or this flash model has huge number of parameters or something.
Or could it be that it's using tool calls in reasoning (e.g. a google search)?
reply▲This will be fantastic for voice. I presume Apple will use it
reply▲>or some sort of cracked way to pack a ton of parametric knowledge into a Flash Model.
More experts with a lower pertentage of active ones -> more sparsity.
Does anyone else understand what the difference is between Gemini 3 'Thinking' and 'Pro'? Thinking "Solves complex problems" and Pro "Thinks longer for advanced math & code".
I assume that these are just different reasoning levels for Gemini 3, but I can't even find mention of there being 2 versions anywhere, and the API doesn't even mention the Thinking-Pro dichotomy.
It seems:
- "Thinking" is Gemini 3 Flash with higher "thinking_level"
- Prop is Gemini 3 Pro. It doesn't mention "thinking_level" but I assume it is set to high-ish.
I think:
Fast = Gemini 3 Flash without thinking (or very low thinking budget)
Thinking = Gemini 3 flash with high thinking budget
Pro = Gemini 3 Pro with thinking
caminanteblanco12 minutes ago
[-] Thank you! I wish they had clearer labelling (or at the very least some documentation) explaining this.
reply▲Really stupid question: How is Gemini-like 'thinking' separate from artificial general intelligence (AGI)?
When I ask Gemini 3 Flash this question, the answer is vague but agency comes up a lot. Gemini thinking is always triggered by a query.
This seems like a higher-level programming issue to me. Turn it into a loop. Keep the context. Those two things make it costly for sure. But does it make it an AGI? Surely Google has tried this?
Quick pricing comparison:
https://www.llm-prices.com/#it=100000&ot=10000&sel=gemini-3-...It's 1/4 the price of Gemini 3 Pro ≤200k and 1/8 the price of Gemini 3 Pro >200k - notable that the new Flash model doesn’t have a price increase after that 200,000 token point.
It’s also twice the price of GPT-5 Mini for input, half the price of Claude 4.5 Haiku.
primaprashant3 hours ago
[-] Pricing is $0.5 / $3 per million input / output tokens. 2.5 Flash was $0.3 / $2.5. That's 66% increase in input tokens and 20% increase in output token pricing.
For comparison, from 2.5 Pro ($1.25 / $10) to 3 Pro ($2 / $12), there was 60% increase in input tokens and 20% increase in output tokens pricing.
Calculating price increases is made more complex by the difference in token usage. From
https://blog.google/products/gemini/gemini-3-flash/ :
> Gemini 3 Flash is able to modulate how much it thinks. It may think longer for more complex use cases, but it also uses 30% fewer tokens on average than 2.5 Pro.
Tiberium33 minutes ago
[-] Yes, but also most of the increase in 3 Flash is in the input context price, which isn't affected by reasoning.
reply▲Glad to see big improvement in the SimpleQA Verified benchmark (28->69%), which is meant to measure factuality (built-in, i.e. without adding grounding resources). That's one benchmark where all models seemed to have low scores until recently. Can't wait to see a model go over 90%... then will be years till the competition is over number of 9s in such a factuality benchmark, but that'd be glorious.
reply▲meetpateltech4 hours ago
[-] reply▲For anyone from the Gemini team reading this: these links should all be prominent in the announcement posts. I always have to hunt around for them!
reply▲meetpateltech3 hours ago
[-] Google actually does something similar for major releases - they publish a dedicated collection page with all related links.
For example, the Gemini 3 Pro collection: https://blog.google/products/gemini/gemini-3-collection/
But having everything linked at the bottom of the announcement post itself would be really great too!
Sadly there's nothing about Gemini 3 Flash on that page yet.
reply▲outside23442 hours ago
[-] I don't want to say OpenAI is toast for general chat AI, but it sure looks like they are toast.
reply▲Wild how this beats 2.5 Pro in every single benchmark. Don't think this was true for Haiku 4.5 vs Sonnet 3.5.
reply▲FergusArgyll3 hours ago
[-] Sonnet 3.5 might have been better than opus 3. That's my recollection anyhow
reply▲At this point in time I start to believe OAI is very much behind on the models race and it can't be reversed
Image model they have released is much worse than nano banana pro, ghibli moment did not happen
Their GPT 5.2 is obviously overfit on benchmarks as a consensus of many developers and friends I know. So Opus 4.5 is staying on top when it comes to coding
The weight of the ads money from google and general direction + founder sense of Brin brought the google massive giant back to life.
None of my companies workflow run on OAI GPT right now. Even though we love their agent SDK, after claude agent SDK it feels like peanuts.
I'm actually liking 5.2 in Codex. It's able to take my instructions, do a good job at planning out the implementation, and will ask me relevant questions around interactions and functionality. It also gives me more tokens than Claude for the same price. Now, I'm trying to white label something that I made in Figma so my use case is a lot different from the average person on this site, but so far it's my go to and I don't see any reason at this time to switch.
reply▲I've noticed when it comes to evaluating AI models, most people simply don't ask difficult enough questions. So everything is good enough, and the preference comes down to speed and style.
It's when it becomes difficult, like in the coding case that you mentioned, that we can see the OpenAI still has the lead. The same is true for the image model, prompt adherence is significantly better than Nano Banana. Especially at more complex queries.
I have a very complex set of logic puzzles I run through my own tests.
My logic test and trying to get an agent to develop a certain type of ** implementation (that is published and thus the model is trained on to some limited extent) really stress test models, 5.2 is a complete failure of overfitting.
Really really bad in an unrecoverable infinite loop way.
It helps when you have existing working code that you know a model can't be trained on.
It doesn't actually evaluate the working code it just assumes it's wrong and starts trying to re-write it as a different type of **.
Even linking it to the explanation and the git repo of the reference implementation it still persists in trying to force a different **.
This is the worst model since pre o3. Just terrible.
Is there a "good enough" endgame for LLMs and AI where benchmarks stop mattering because end users don't notice or care? In such a scenario brand would matter more than the best tech, and OpenAI is way out in front in brand recognition.
reply▲Google biggest advantage over time will be costs. They have their own hardware which they can and will optimise for their LLMS. And Google has experience of getting market share over time by giving better results, performance or space. ie gmail vs hotmail/yahoo. Chrome vs IE/Firefox. So don't discount them if the quality is better they will get ahead over time.
reply▲For average consumers, I think very much yes, and this is where OpenAI's brand recognition shines.
But for anyone using LLM's to help speed up academic literature reviews where every detail matters, or coding where every detail matters, or anything technical where every detail matters -- the differences very much matter. And benchmarks serve just to confirm your personal experience anyways, as the differences between models becomes extremely apparent when you're working in a niche sub-subfield and one model is showing glaring informational or logical errors and another mostly gets it right.
And then there's a strong possibility that as experts start to say "I always trust <LLM name> more", that halo effect spreads to ordinary consumers who can't tell the difference themselves but want to make sure they use "the best" -- at least for their homework. (For their AI boyfriends and girlfriends, other metrics are probably at play...)
> OpenAI's brand recognition shines.
We've seen this movie before. Snapchat was the darling. Infact, it invented the entire category and was dominating the format for years. Then it ran out of time.
Now very few people use Snapchat, and it has been reduced to a footnote in history.
If you think I'm exaggerating, that just proves my point.
decimalenough1 hour ago
[-] Not a great example: Snapchat made it through the slump, successfully captured the next generation of teenagers, and now has around 500M DAUs.
reply▲I haven't seen any LLM tech shine "where every detail matters".
In fact so far, they consistently fail in exactly these scenario, glossing over random important details whenever you double check results in depth.
You might have found models, prompts or workflows that work for you though, I'm interested.
That might be true for a narrow definition of chatbots, but they aren't going to survive on name recognition if their models are inferior in the medium term. Right now, "agents" are only really useful for coding, but when they start to be adopted for more mainstream tasks, people will migrate to the tools that actually work first.
reply▲this. I don't know any non-tech people who use anything other than chatgpt. On a similar note, I've wondered why Amazon doesn't make a chatgpt-like app with their latest Alexa+ makeover, seems like a missed opportunity. The Alexa app has a feature to talk to the LLM in chat mode, but the overall app is geared towards managing devices.
reply▲Google has great distribution to be able to just put Gemini in front of people who are already using their many other popular services. ChatGPT definitely came out of the gate with a big lead on name recognition, but I have been surprised to hear various non-techy friends talking about using Gemini recently, I think for many of them just because they have access at work through their Workspace accounts.
reply▲Most of Europe if full of Gemini ads, my parents use Gemini because it is free and it popped up in YouTube ad before the video
Just go outside the bubble plus take a bit older people
I doubt anyone I know who is using llms outside of work knows that there are benchmark tests for these models.
reply▲This is why both google and microsoft are pushing Gemini and Copilot in everyone's face.
reply▲"At this point in time I start to believe OAI is very much behind on the models race and it can't be reversed"
This has been true for at least 4 months and yeah, based on how these things scale and also Google's capital + in-house hardware advantages, it's probably insurmountable.
OAI also got talent mined. Their top intellectual leaders left after fight with sama, then Meta took a bunch of their mid-senior talent, and Google had the opposite. They brought Noam and Sergey back.
reply▲Yeah the only thing standing in Google's way is Google. And it's the easy stuff, like sensible billing models, easy to use docs and consoles that make sense and don't require 20 hours to learn/navigate, and then just the slew of bugs in Gemini CLI that are basic usability and model API interaction things. The only differentiator that OpenAI still has is polish.
Edit: And just to add an example: openAI's Codex CLI billing is easy for me. I just sign up for the base package, and then add extra credits which I automatically use once I'm through my weekly allowance. With Gemini CLI I'm using my oauth account, and then having to rotate API keys once I've used that up.
Also, Gemini CLI loves spewing out its own chain of thought when it gets into a weird state.
Also Gemini CLI has an insane bias to action that is almost insurmountable. DO NOT START THE NEXT STAGE still has it starting the next stage.
Also Gemini CLI has been terrible at visibility on what it's actually doing at each step - although that seems a bit improved with this new model today.
mips_avatar2 hours ago
[-] I'd be curious how many people use openrouter byok just to avoid figuring out the cloud consoles for gcp/azure.
reply▲I do. Gave up using Gemini directly.
reply▲Agreed. It's ridiculous.
reply▲Is there anything pointing to Brin having anything to do with Google’s turnaround in AI? I hear a lot of people saying this, but no one explaining why they do
reply▲In organizations, everyone's existence and position is politically supported by their internal peers around their level. Even google's & microsoft's current CEOs are supported by their group of co-executives and other key players. The fact that both have agreeable personalities is not a mistake! They both need to keep that balance to stay in power, and that means not destroying or disrupting your peer's current positions. Everything is effectively decided by informal committee.
Founders are special, because they are not beholden to this social support network to stay in power and founders have a mythos that socially supports their actions beyond their pure power position. The only others they are beholden too are their co-founders, and in some cases major investor groups. This gives them the ability to disregard this social balance because they are not dependent on it to stay on power. Their power source is external to the organization, while everyone else is internal to it.
This gives them a very special "do something" ability that nobody else has. It can lead to failures (zuck & occulus, snapchat spectacles) or successes (steve jobs, gemini AI), but either way, it allows them to actually "do something".
>
Founders are special, because they are not beholden to this social support network to stay in powerOf course they are. Founders get fired all the time. As often as non-founder CEOs purge competition from their peers.
> The only others they are beholden too are their co-founders, and in some cases major investor groups
This describes very few successful executives. You can have your co-founders and investors on board, if your talent and customers hate you, they’ll fuck off.
If he's having an impact it's because he can break through the bureaucracy. He's not trying to protect a fiefdom.
reply▲I would say it more goes back to the Google Brain + DeepMind merger, creating Google DeepMind headed by Demis Hassabis.
The merger happened in April 2023.
Gemini 1.0 was released in Dec 2023, and the progress since then has been rapid and impressive.
>
I start to believe OAI is very much behindKara Swisher recently compared OpenAI to Netscape.
GPT 5.2 is actually getting me better outputs than Opus 4.5 on very complex reviews (on high, I never use less) - but the speed makes Opus the default for 95% of use cases.
reply▲That's a quite sensationalized view.
Ghibli moment was only about half a year ago. At that moment, OpenAI was so far ahead in terms of image editing. Now it's behind for a few months and "it can't be reversed"?
Check the size and budget of Google iniatives. It’s unlimited
reply▲i think the most important part of google vs openai is slowing usage of consumer LLMs. people focus on gemini's growth, but overall LLM MAUs and time spent is stabilizing. in aggregate it looks like a complete s-curve. you can kind of see it in the table in the link below but more obvious when you have the sensortower data for both MAUs and time spent.
the reason this matters is slowing velocity raises the risk of featurization, which undermines LLMs as a category in consumer. cost efficiency of the flash models reinforces this as google can embed LLM functionality into search (noting search-like is probably 50% of chatgpt usage per their july user study). i think model capability was saturated for the average consumer use case months ago, if not longer, so distribution is really what matters, and search dwarfs LLMs in this respect.
https://techcrunch.com/2025/12/05/chatgpts-user-growth-has-s...
Add This to Gemini distribution which is being adcertised by Google in all of their products, and average Joe will pick the sneakers at the shelf near the checkout rather than healthier option in the back
reply▲Those darn sneakers are just too delicious!
reply▲That's not how the arena works. The evaluation is blind so Google's advertising/integration has no effect on the results.
reply▲3 points, sure
reply▲Right, it only scores 3 points higher on image edit, which is within the margin of error. But on image generation, it scores a significant 29 points higher.
reply▲...and what does this have to do with the comment you replied to? Did you reply to the wrong person or you were just stating unrelated factoids?
reply▲the trend I've seen is that none of these companies are behind in concept and theory, they are just spending longer intervals baking a more superior foundational model
so they get lapped a few times and then drop a fantastic new model out of nowhere
the same is going to happen to Google again, Anthropic again, OpenAI again, Meta again, etc
they're all shuffling the same talent around, its California, that's how it goes, the companies have the same institutional knowledge - at least regarding their consumer facing options
random97498322 hours ago
[-] This is obviously trained on Pro 3 outputs for benchmaxxing.
reply▲Not trained on pro, distilled from it.
reply▲What do you think distilled means...?
reply▲NitpickLawyer1 hour ago
[-] > for benchmaxxing.
Out of all the big4 labs, google is the last I'd suspect of benchmaxxing. Their models have generally underbenched and overdelivered in real world tasks, for me, ever since 2.5 pro came out.
Google has incredible tech. The problem is and always has been their products. Not only are they generally designed to be anti-consumer, but they go out of their way to make it as hard as possible. The debacle with Antigravity exfiltrating data is just one of countless.
reply▲The Antigravity case feels like a pure bug and them rushing to market. They had a bunch of other bugs showing that. That is not anti-consumer or making it difficult.
reply▲tootyskooty3 hours ago
[-] Since it now includes 4 thinking levels (minimal-high) I'd really appreciate if we got some benchmarks across the whole sweep (and not just what's presumably high).
Flash is meant to be a model for lower cost, latency-sensitive tasks. Long thinking times will both make TTFT >> 10s (often unacceptable) and also won't really be that cheap?
happyopossum2 hours ago
[-] Google appears to be changing what flash is “meant for” with this release - the capability it has along with the thinking budgets make it superior to previous Pro models in both outcome and speed. The likely-soon-coming flash-lite will fit right in to where flash used to be - cheap and fast.
reply▲SyrupThinker3 hours ago
[-] I wonder if this suffers from the same issue as 3 Pro, that it frequently "thinks" for a long time about date incongruity, insisting that it is 2024, and that information it receives must be incorrect or hypothetical.
Just avoiding/fixing that would probably speed up a good chunk of my own queries.
Omg, it was so frustrating to say:
Summarize recent working arxiv url
And then it tells me the date is from the future and it simply refuses to fetch the URL.
Thinking along the line of speed, I wonder if a model that can reason and use tools at 60fps would be able to control a robot with raw instructions and perform skilled physical work currently limited by the text-only output of LLMs. Also helps that the Gemini series is really good at multimodal processing with images and audio. Maybe they can also encode sensory inputs in a similar way.
Pipe dream right now, but 50 years later? Maybe
Much sooner, hardware, power, software, even AI model design, inference hardware, cache, everything being improved , it's exponential.
reply▲Looks like a good workhorse model, like I felt 2.5 Flash also was at its time of launch. I hope I can build confidence with it because it'll be good to offload Pro costs/limits as well of course always nice with speed for more basic coding or queries. I'm impressed and curious about the recent extreme gains on ARC-AGI-2 from 3 Pro, GPT-5.1 and now even 3 Flash.
reply▲I think about what would be most terrifying to Anthropic and OpenAI i.e. The absolute scariest thing that Google could do. I think this is it: Release low latency, low priced models with high cognitive performance and big context window, especially in the coding space because that is direct, immediate, very high ROI for the customer.
Now, imagine for a moment they had also vertically integrated the hardware to do this.
JumpCrisscross2 hours ago
[-] >
think about what would be most terrifying to Anthropic and OpenAIThe most terrifying thing would be Google expanding its free tiers.
"Now, imagine for a moment they had also vertically integrated the hardware to do this."
Then you realise you aren't imagining it.
iwontberude2 hours ago
[-] “And then imagine Google designing silicon that doesn’t trail the industry. While you are there we may as well start to imagine Google figures out how to support a product lifecycle that isn’t AdSense”
Google is great on the data science alone, every thing else is an after thought
It's not funny when I have to explain the joke.
reply▲Oh I got your joke, sir - but as you can see from the other comment, there are techies who still don't have even a rudimentary understanding of tensor cores, let alone the wider public and many investors. Over the next year or two the gap between Google and everybody else, even those they license their hardware to, is going to explode.
reply▲Exactly my point, they have bespoke offerings but when they compete head to head for performance they get smoked. See more: their Tensor processor that they use in the beleaguered Pixel. They are in last place.
TPUs on the other hand are ASICs, we are more than familiar with the limited application, high performance and high barriers to entry associated with them. TPUs will be worthless as the AI bubble keeps deflating and excess capacity is everywhere.
The people who don't have a rudimentary understanding are the wall street boosters that treat it like the primary threat to Nvidia or a moat for Google (hint: it is neither).
It's fast and good in Gemini CLI (even though Gemini CLI still lags far behind Claude as a harness).
reply▲I remember the preview price for 2.5 flash was much cheaper. And then it got quite expensive when it went out of preview. I hope the same won't happen.
reply▲Tiberium30 minutes ago
[-] For 2.5 Flash Preview the price was specifically much cheaper for the no-reasoning mode, in this case the model reasons by default so I don't think they'll increase the price even further.
reply▲For someone looking to switch over to Gemini from OpenAI, are there any gotchas one should be aware of? E.g. I heard some mention of API limits and approvals? Or in terms of prompt writing? What advice do people have?
reply▲scrollop55 minutes ago
[-] https://epoch.ai/benchmarks/simplebenchJust do it.
I use a service where I have access to all SOTA models and many open sourced models, so I change models within chats, using MCPs eg start a chat with opus making a search with perplexity and grok deepsearch MCPs and google search, next query is with gpt 5 thinking Xhigh, next one with gemini 3 pro, all in the same conversation. It's fantastic! I can't imagine what it would be like again to be locked into using one (or two) companies. I have nothing to do with the guys who run it (the hosts from the podcast This day in AI, though if you're interested have a look in the simtheory.ai discord.
I don't know how people use one service can manage...
reply▲99% of what I do is fine-tuned models, so there is a certain level of commitment I have to make around training and time to switch.
reply▲OpenAI is pretty firmly in the rear-view mirror now.
reply▲walthamstow3 hours ago
[-] Google Antigravity is a buggy mess at the moment, but I believe it will eventually eat Cursor as well. The £20/mo tier currentluy has the highest usage limits on the market, including Google models and Sonnet and Opus 4.5.
reply▲I've been using the preview flash model exclusively since it came out, the speed and quality of response is all I need at the moment. Although still using Claude Code w/ Opus 4.5 for dev work.
Google keeps their models very "fresh" and I tend to get more correct answers when asking about Azure or O365 issues, ironically copilot will talk about now deleted or deprecated features more often.
I've found copilot within the Azure portal to be basically useless for solving most problems.
reply▲Me too. I don't understand why companies think we devs need a custom chat on their website when we all have access to a chat with much smarter models open in a different tab.
reply▲That's not what they are thinking. They are thinking: "We want to capture the dev and make them use our model – since it is easier to use it in our tab, it can afford to be inferior. This way we get lots of tasty, tasty user data."
reply▲I really wish these models were available via AWS or Azure. I understand strategically that this might not make sense for Google, but at a non-software-focused F500 company it would sure make it a lot easier to use Gemini.
reply▲I feel like that is part of their cloud strategy. If your company wants to pump a huge amount of data through one of these you will pay a premium in network costs. Their sales people will use that as a lever for why you should migrate some or all of your fleet to their cloud.
reply▲jiggawatts27 minutes ago
[-] A few gigabytes of text is practically free to transfer even over the most exorbitant egress fee networks, but would cost “get finance approval” amounts of money to process even through a cheaper model.
reply▲Ok, I was a bit addicted to Opus 4.5 and was starting to feel like there's nothing like it.
Turns out Gemini 3 Flash is pretty close. The Gemini CLI is not as good but the model more than makes up for it.
The weird part is Gemini 3 Pro is nowhere as good an experience. Maybe because its just so slow.
scrollop53 minutes ago
[-] Yes! Gemini 3 pro is significantly slower than opus (surprisingly) , and prefer opus' output.
Might be using flash for my MCP research/transcriber/minor tasks modl over haiku, now, though (will test of course)
I will have to try that. Cursor bill got pretty high with Opus 4.5. Never considered opus before the 4.5 price drop but now it's hard to change... :)
reply▲diamondfist252 hours ago
[-] $100 Claude max is the best subscription I’ve ever had.
Well worth every penny now
I’m wondering why Claude Opus 4.5 is missing from the benchmarks table.
reply▲I wondered this, too. I think the emphasis here was on the faster / lower costs models, but that would suggest that Haiku 4.5 should be the Anthropic entry on the table instead. They also did not use the most powerful xAI model either, instead opting for the fast one. Regardless, this new Gemini 3 Flash model is good enough that Anthropic should be feeling pressure on both price and model output quality simultaneously regardless of which Anthropic model is being compared against, which is ultimately good for the consumer at the end of the day.
reply▲doomerhunter4 hours ago
[-] Pretty stoked for this model. Building a lot with "mixture of agents" / mix of models and Gemini's smaller models do feel really versatile in my opinion.
Hoping that the local ones keep progressively up (gemma-line)
bennydog2244 hours ago
[-] From the article, speed & cost match 2.5 Flash. I'm working on a project where there's a huge gap between 2.5 Flash and 2.5 Flash Lite as far as performance and cost goes.
-> 2.5 Flash Lite is super fast & cheap (~1-1.5s inference), but poor quality responses.
-> 2.5 Flash gives high quality responses, but fairly expensive & slow (5-7s inference)
I really just need an in-between for Flash and Flash Lite for cost and performance. Right now, users have to wait up to 7s for a quality response.
so hat's why logan posed 3 lightning emojis. at $0.50/M for input and $3.00/M for output, this will put serious pressure on OpenAI and Anthropic now
its almost as good as 5.2 and 4.5 but way faster and cheaper
It is interesting to see the "DeepMind" branding completely vanish from the post. This feels like the final consolidation of the Google Brain merger. The technical report mentions a new "MoE-lite" architecture. Does anyone have details on the parameter count? If this is under 20B params active, the distillation techniques they are using are lightyears ahead of everyone else.
reply▲This is the first flash/mini model that doesn't make a complete ass of itself when I prompt for the following: "Tell me as much as possible about Skatval in Norway. Not general information. Only what is uniquely true for Skatval."
Skatval is a small local area I live in, so I know when it's bullshitting. Usually, I get a long-winded answer that is PURE Barnum-statement, like "Skatval is a rural area known for its beautiful fields and mountains" and bla bla bla.
Even with minimal thinking (it seems to do none), it gives an extremely good answer. I am really happy about this.
I also noticed it had VERY good scores on tool-use, terminal, and agentic stuff. If that is TRUE, it might be awesome for coding.
I'm tentatively optimistic about this.
I tried the same with my father's little village (Zarza Capilla, in Spain), and it gave a surprisingly good answer in a couple of seconds. Amazing.
reply▲That's a really cool prompt idea, I just tried it with my neighborhood and it nailed it. Very impressive.
reply▲You are effectively describing SimpleQA but with a single question instead of a comprehensive benchmark and you can note the dramatic increase in performance there.
reply▲Two quick questions to Gemini/AI Studio users:
1, has anyone actually found 3 Pro better than 2.5 (on non code tasks)? I struggle to find a difference beyond the quicker reasoning time and fewer tokens.
2, has anyone found any non-thinking models better than 2.5 or 3 Pro? So far I find the thinking ones significantly ahead of non thinking models (of any company for that matter.)
Workaccount24 hours ago
[-] Gemini 3 is a step change up against 2.5 for electrical engineering R&D.
reply▲I think it's probably actually better at math. Though still not enough to be useful in my research in a substantial way. Though I suspect this will change suddenly at some point as the models move past a certain threshold (also it is heavily limited by the fact that the models are very bad at not giving wrong proofs/counterexamples) so that even if the models are giving useful rates of successes, the labor to sort through a bunch of trash makes it hard to justify.
reply▲Not for coding but for the design aspect, 3 outshines 2.5
reply▲Consolidating their lead. I'm getting really excited about the next Gemma release.
reply▲prompt_god25 minutes ago
[-] it's better than Pro in a few evals. anyone who used, how is it for coding?
reply▲hubraumhugo3 hours ago
[-] reply▲Pretty fucking hilarious, if completely off-topic.
reply▲This is exactly why you keep your personal life off the internet
reply▲This is hilarious. The personalized pie charts and XKCD-style comics are great, and the roast-style humor is perfect.
I do feel like it's not an entirely accurate caricature (recency bias? limited context?), but it's close enough.
Good work!
You should do a "show HN" if you're not worried about it costing you too much.
This is great. I literally "LOL'd".
reply▲Workaccount24 hours ago
[-] Really hoping this is used for real time chatting and video. The current model is decent, but when doing technical stuff (help me figure out how to assemble this furniture) it falls far short of 3 pro.
reply▲Will be interesting to see what their quota is. Gemini 3.0 Pro only gives you 250 / day until you spam them with enough BS requests to increase your total spend > $250.
reply▲Gemini 3 are great models but lacking a few things:
- app expirience is atrocious, poor UX all over the place. A few examples: silly jumps when reading the text when the model starting to respond, slide-over view in iPad breaking request while Claude and ChatGPT working fine.
- Google offer 2 choices: your data used for whatever they want or if you want privacy, the app expirience going even worse.
reply▲walthamstow3 hours ago
[-] I'm sure it's good, I thought the last one was too, but it seems like the backdoor way to increase prices is to release a new model
reply▲If the model is better in that it resolves the task with fewer iterations then the i/o token pricing may be a wash or lower.
reply▲FergusArgyll3 hours ago
[-] So much for "Monopolies get lazy, they just rent seek and don't innovate"
reply▲jonathan_h18 minutes ago
[-] "Monopolies get lazy, they just rent seek and don't innovate"
I think part of what enables a monopoly is absence of meaningful competition, regardless of how that's achieved -- significant moat, by law or regulation, etc.
I don't know to what extent Google has been rent-seeking and not innovating, but Google doesn't have the luxury to rent-seek any longer.
NitpickLawyer3 hours ago
[-] Also so much for the "wall, stagnation, no more data" folks. Womp womp.
reply▲Monopolies and wanna-be monopolies on the AI-train are running for their lives. They have to innovate to be the last one standing (or second last) - in their mind.
reply▲The LLM market has no moats so no one "feels" like a monopoly, rightfully.
reply▲LLMs are a big threat to their search engine revenue, so whatever monopoly Google may have had does not exist anymore.
reply▲Does this imply we don't need as much compute for models/agents? How can any other AI model compete against that?
reply▲jdthedisciple1 hour ago
[-] To those saying "OpenAI is toast"
ChatGPT still has 81% market share as of this very moment, vs Gemini's ~2%, and arguably still provides the best UX and branding.
Everyone and their grandma knows "ChatGPT", who outside developers' bubble has even heard of Gemini Flash?
Yea I don't think that dynamic is switching any time soon.
riku_iki43 minutes ago
[-] > ChatGPT still has 81% market share as of this very moment, vs Gemini's ~2%
where did you get this from?
Looks awesome on paper. However, after trying it on my usual tasks, it is still very bad at using the French language, especially for creative writing. The gap between the Gemini 3 family and GPT-5 or Sonnet 4.5 is important for my usage.
Also, I hate that I cannot send the Google models in a "Thinking" mode like in ChatGPT. When I send GPT 5.1 Thinking on a legal task and tell it to check and cite all sources, it takes +10 minutes to answer, but it did check everything and cite all its sources in the text; whereas the Gemini models, even 3 Pro, always answer after a few seconds and never cite their sources, making it impossible to click to check the answer. It makes the whole model unusable for these tasks.
(I have the $20 subscription for both)
happyopossum2 hours ago
[-] > whereas the Gemini models, even 3 Pro, always answer after a few seconds and never cite their sources
Definitely has not been my experience using 3 Pro in Gemini Enterprise - in fact just yesterday it took so long to do a similar task I’d thought something was broken. Nope, just re-chrcking a source
Does Gemini Enterprise have more features?
Just tried once again with the exact same prompt: GPT-5.1-Thinking took 12m46s and Gemini 3.0 Pro took about 20 seconds. The latter obviously has a dramatically worse answer as a result.
(Also, the thinking trace is not in the correct language, and doesn't seem to show which sources have been read at which steps- there is only a "Sources" tab at the end of the answer.)
retinaros49 minutes ago
[-] i might have missed the bandwagon on gemini but I never found the models to be reliable. now it seems they rank first in some hallucinations bench?
I just always thought the taste of gpt or claude models was more interesting in the professional context and their end user chat experience more polished.
are there obvious enterprise use cases where gemini models shine?
Yet again Flash receives a notable price hike: from $0.3/$2.5 for 2.5 Flash to $0.5/$3 (+66.7% input, +20% output) for 3 Flash. Also, as a reminder, 2 Flash used to be $0.1/$0.4.
reply▲Yes, but
this Flash is a lot more powerful - beating Gemini 3 Pro on some benchmarks (and pretty close on others).
I don't view this as a "new Flash" but as "a much cheaper Gemini 3 Pro/GPT-5.2"
Right, depends on your use cases. I was looking forward to the model as an upgrade to 2.5 Flash, but when you're processing hundreds of millions of tokens a day (not hard to do if you're dealing in documents or emails with a few users), the economics fall apart.
reply▲I would be less salty if they gave us 3 Flash Lite at same price as 2.5 Flash or cheaper with better capability, but they still focus on the pricier models :(
reply▲Same! I want to do some data stuff from documents and 2.0 pricing was amazing, but the constant increases go the wrong way for this task :/
reply▲Sadly not available in the free tier...
reply▲Any word on if this using their diffusion architecture?
reply▲JeremyHerrman3 hours ago
[-] Disappointed to see continued increased pricing for 3 Flash (up from $0.30/$2.50 to $0.50/$3.00 for 1M input/output tokens).
I'm more excited to see 3 Flash Lite. Gemini 2.5 Flash Lite needs a lot more steering than regular 2.5 Flash, but it is a very capable model and combined with the 50% batch mode discount it is CHEAP ($0.05/$0.20).
Have you seen any indications that there will be a Lite version?
reply▲summerlight2 hours ago
[-] I guess if they want to eventually deprecate the 2.5 family they will need to provide a substitute. And there are huge demands for cheap models.
reply▲So is Gemini 3 Fast the same as Gemini 3 Flash?
reply▲They went too far, now the Flash model is competing with their Pro version. Better SWE-bench, better ARC-AGI 2 than 3.0 Pro. I imagine they are going to improve 3.0 Pro before it's no more in Preview.
Also I don't see it written in the blog post but Flash supports more granular settings for reasoning: minimal, low, medium, high (like openai models), while pro is only low and high.
"minimal" is a bit weird.
> Matches the “no thinking” setting for most queries. The model may think very minimally for complex coding tasks. Minimizes latency for chat or high throughput applications.
I'd prefer a hard "no thinking" rule than what this is.
It still supports the legacy mode of setting the budget, you can set it to 0 and it would be equivalent to none reasoning effort like gpt 5.1/5.2
reply▲I can confirm this is the case via the API, but annoyingly AI Studio doesn't let you do so.
reply▲> They went too far, now the Flash model is competing with their Pro version
Wasn't this the case with the 2.5 Flash models too? I remember being very confused at that time.
JohnnyMarcone2 hours ago
[-] This is similar to how Anthropic has treated sonnet/opus as well. At least pre opus 4.5.
To me it seems like the big model has been "look what we can do", and the smaller model is "actually use this one though".
I'm not sure how I'm going to live with this!
reply▲I tried Gemini CLI the other day, typed in two one line requests, then it responded that it would not go further because I ran out of tokens. I've hard other people complaint that it will re-write your entire codebase from scratch and you should make backups before even starting any code-based work with the Gemini CLI. I understand they are trying to compete against Claude Code, but this is not ready for prime time IMHO.
reply▲I never have, do not, and conceivably never will use gemini models, or any other models that require me to perform inference on Alphabet/Google's servers (i.e. gemma models I can run locally or on other providers are fine), but kudos to the team over there for the work here, this does look really impressive. This kind of competition is good for everyone, even people like me who will probably never touch any gemini model.
reply▲oklahomasports2 hours ago
[-] You don’t want Google to know that you are searching for like advice on how much a 61 yr old can contribute to a 401k. What are you hiding?
reply▲Why do you close the bathroom stall door in public?
You're not doing anything wrong. Everyone knows what you're doing. You have no secrets to hide.
Yet you value your privacy anyway. Why?
Also - I have no problem using Anthropic's cloud-hosted services. Being opposed to some cloud providers doesn't mean I'm opposed to all cloud providers.
Is there a way to try this without a Google account?
reply▲Just use openrouter or a similar aggregator.
reply▲this is why samsung is stopping production in flash
reply▲This is why they stopped The Flash after season 9 in 2023.
reply