The benchmarks are not particularly impressive. I suppose they needed to release something since the long pause. But not clear why would I use it now.
dumberquestions
"..and in some benchmarks like DeepSWE by Datacurve, we observe up to 65%, all at a lower cost per output token." "3.6 Flash delivers higher precision with fewer unwanted code edits and reduced execution loops, as seen in DeepSWE (49% vs. 37%)" So which one is it? 65% or 49%?
jgbuddy
It is both less intelligent and more expensive than GLM-5.2, while being closed weight.
metalliqaz
Other discussion from a few minutes earlier: https://news.ycombinator.com/item?id=48993130
velominati
Wow - Google does not even bother to show benchmarks of these models compared to the frontier and Chinese labs - only against previous versions. I'm not surprised. Having worked there for years it was amazing just how inwardly looking the company is.
dvduval
It does seem like their releases are getting closer together. I get the feeling they realized they were trying to roll out to their entire ecosystem and now they’re focusing more just directly on the AI model itself. I think give it a little time and they’ll start to be one of the competitors too.
singingtoday
I'm more excited for 3.5 pro. Gemini has fallen behind in some areas, but is still one of the best multimodal models. Has anybody found any models better at image or audio analysis?
npn
tested the models on aistudio. despite that the knowledge cut off is march 2026 it still knows nothing about 2025! you can check by asking "list notable world events in 2025, only list unplanned" on aistudio. or you can ask for Charlie Kirk, it also does not know. I tried it multiple time to ensure that I didn't not get routed to older models! > but google has search irrelevant, without deeper knowledge about cutting edge technologies or latest libraries, all of it suggestions are crap. even you ask it to search it will still use outdated keyword thus only getting outdated information. in other word, what a disaster!
nsbk
It is 17% more token-efficient than 3.5 and performs significantly better in coding and tool usage benchmarks. It is also cheaper than 3.5: > This enhanced efficiency is also combined with a lower price than 3.5 Flash. At $1.50/1M input tokens and $7.50/1M output tokens, 3.6 Flash reduces the overall cost per agentic task, making agents more cost-effective to build and run.
It's a bit disheartening to see no comparison to other models here - and I'm not sure this pushes the curve anywhere. 3.6 flash is more expensive than GLM 5.2 - but seemingly worse, although this post is really light (lite?) on details. It seemed for a time that Google had finally gotten the ball rolling, but I'm doubting that more and more as time passes. We'll see what happens with 3.5 pro I suppose.
b473a
No word about updating Jules, which is still stuck on 3.1 Pro. I get that it's probably niche but I've really appreciated basically being able to give directions to Jules on my phone, then reviewing and merging a GitHub PR fifteen minutes later. It's been great for getting some progress in on a few personal projects during my commute when I can't exactly pull out my laptop. Anyone have any good alternatives?
geooff_
At this point just put the Pareto in the bag bruh
ConfusedDog
Why would 3.6 flash perform a little worse than 3.5 flash on Artificial Analysis Coding Index... https://artificialanalysis.ai/models/gemini-3-6-flash?intell...
dankai
Unfortunately says more about how competitive 3.5 pro would be today at the frontier if they forgo it for 3.6 flash.
catigula
"We made 3.6/4 Pro, but it sucks, so this is the distilled model" vibes.
mfkrause
Pretty underwhelming, as expected honestly. I don't want to know what morale is like at DeepMind right now.
kilroy123
I deeply wish Google would focus on models like Gemma. Small, powerful, open-weight models you can run on phones or regular computer hardware.
doctoboggan
I have a side business selling custom fingerprint jewelry and I use gemini nano banana to clean up customer submitted fingerprint images. This was a step I used to do by hand at 10 - 15 minutes per image and nano banana is the first model that is able to do the task (it is astonishingly good at it). I can't wait to see what the next nano banana can do, hopefully its released soon.
pietz
Are they comparing 3.6 Flash to 5.6 Luna and losing? That's ruff.
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Discussion Highlights (20 comments)
yanis_t
The benchmarks are not particularly impressive. I suppose they needed to release something since the long pause. But not clear why would I use it now.
dumberquestions
"..and in some benchmarks like DeepSWE by Datacurve, we observe up to 65%, all at a lower cost per output token." "3.6 Flash delivers higher precision with fewer unwanted code edits and reduced execution loops, as seen in DeepSWE (49% vs. 37%)" So which one is it? 65% or 49%?
jgbuddy
It is both less intelligent and more expensive than GLM-5.2, while being closed weight.
metalliqaz
Other discussion from a few minutes earlier: https://news.ycombinator.com/item?id=48993130
velominati
Wow - Google does not even bother to show benchmarks of these models compared to the frontier and Chinese labs - only against previous versions. I'm not surprised. Having worked there for years it was amazing just how inwardly looking the company is.
dvduval
It does seem like their releases are getting closer together. I get the feeling they realized they were trying to roll out to their entire ecosystem and now they’re focusing more just directly on the AI model itself. I think give it a little time and they’ll start to be one of the competitors too.
singingtoday
I'm more excited for 3.5 pro. Gemini has fallen behind in some areas, but is still one of the best multimodal models. Has anybody found any models better at image or audio analysis?
npn
tested the models on aistudio. despite that the knowledge cut off is march 2026 it still knows nothing about 2025! you can check by asking "list notable world events in 2025, only list unplanned" on aistudio. or you can ask for Charlie Kirk, it also does not know. I tried it multiple time to ensure that I didn't not get routed to older models! > but google has search irrelevant, without deeper knowledge about cutting edge technologies or latest libraries, all of it suggestions are crap. even you ask it to search it will still use outdated keyword thus only getting outdated information. in other word, what a disaster!
nsbk
It is 17% more token-efficient than 3.5 and performs significantly better in coding and tool usage benchmarks. It is also cheaper than 3.5: > This enhanced efficiency is also combined with a lower price than 3.5 Flash. At $1.50/1M input tokens and $7.50/1M output tokens, 3.6 Flash reduces the overall cost per agentic task, making agents more cost-effective to build and run.
ilreb
dupe? https://news.ycombinator.com/item?id=48993130
m_w_
It's a bit disheartening to see no comparison to other models here - and I'm not sure this pushes the curve anywhere. 3.6 flash is more expensive than GLM 5.2 - but seemingly worse, although this post is really light (lite?) on details. It seemed for a time that Google had finally gotten the ball rolling, but I'm doubting that more and more as time passes. We'll see what happens with 3.5 pro I suppose.
b473a
No word about updating Jules, which is still stuck on 3.1 Pro. I get that it's probably niche but I've really appreciated basically being able to give directions to Jules on my phone, then reviewing and merging a GitHub PR fifteen minutes later. It's been great for getting some progress in on a few personal projects during my commute when I can't exactly pull out my laptop. Anyone have any good alternatives?
geooff_
At this point just put the Pareto in the bag bruh
ConfusedDog
Why would 3.6 flash perform a little worse than 3.5 flash on Artificial Analysis Coding Index... https://artificialanalysis.ai/models/gemini-3-6-flash?intell...
dankai
Unfortunately says more about how competitive 3.5 pro would be today at the frontier if they forgo it for 3.6 flash.
catigula
"We made 3.6/4 Pro, but it sucks, so this is the distilled model" vibes.
mfkrause
Pretty underwhelming, as expected honestly. I don't want to know what morale is like at DeepMind right now.
kilroy123
I deeply wish Google would focus on models like Gemma. Small, powerful, open-weight models you can run on phones or regular computer hardware.
doctoboggan
I have a side business selling custom fingerprint jewelry and I use gemini nano banana to clean up customer submitted fingerprint images. This was a step I used to do by hand at 10 - 15 minutes per image and nano banana is the first model that is able to do the task (it is astonishingly good at it). I can't wait to see what the next nano banana can do, hopefully its released soon.
pietz
Are they comparing 3.6 Flash to 5.6 Luna and losing? That's ruff.