> Argon will launch at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off input token price.
That would be great if it can be as good as those models. I was very excited about 3.8 Flash but it doom looped while executing a coding task and I stopped using it then. And will check how the token usage is like for this one.
Trading punches in the benchmarks with Mimo v2.6 and 6.1-Sol (both very cheap!), and decidedly inferior to Opus 5.5. I'm afraid this looks unimpressive. Rather comical that they're delaying its launch "for safety reasons".
What are you talking about? It’s comparable to Opus 5.5 on “high” (54 vs 53; $1.82 vs $1.99), crushes every model except the most modern OAI/Ant ones, has way lower hallucination than every existing model and probably broader support for multimodal like existing Gemini models. This is so ludicrously off base.
From the charts, it's similar in intelligence and cost per task to both Opus 5.5 (high) and 6-Astra (max). It would be better if it were more intelligent and less expensive, but I don't see a reason to expect it to have better performance than models released around the same time.
To play the Devil's advocate, Claude loves chugging tokens, while Gemini appears to be quite a bit more conservative and efficient. I believe AA's price per task breakdown reflects this.
What a snooze fest. Another model that does not meaningfully improve on intelligence or price compared to its peers. Google has basically announced that they've "caught up" with the rest. I think they've been doing great work in the Flash department so seeing this is... underwhelming?
The only models beating it are on "max", while this is "high". There's no guarantee that those effort / reasoning levels compare, but there's almost certainly an "xhigh" or "max" version later which will score higher there.
I found that Google does not benchmaxx as much as the other providers. Of you look at real-case evaluation like lm-arena, even the 3.8 flash is often near the top despite its benchmark index being worse.
I noticed this recently with the user submitted benchmarks on Kaggle. For these obscure tests that the models haven't seen, Gemini 3.8 is often on par or beating other frontier models. Gemini is a bit shite at the game checkers though, for some weird reason it performs poorly on those benchmarks.
Note: Google can sell their tokens at cost if they really want to drive out competition, but long term they are better off by everyone making a healthy margin (and Google does a double-dip by also selling compute, services).
So, like any optimal game theory move, they are better off not starting a price war
Google is losing in the market share - their share is 0. Anthropic revenue was $60B in the last 12 months. Google is not growing the pie, it needs to buy its way to the market share and to a seat in the table.
It's hard to not see this as a gut punch for OpenAI. They're lead was largely captured by scoring on value (by way of reset after reset) and now they're getting eaten up on price and being bestes and equalled on performance. I'll still pay a premium for Opus 5.5 right now because it's nearly unlimited use, but Google is the quiet sleeping king
Everyone is happy to watch everyone else, but I'd wager google burns more tokens through their search product than basically anyone else and now they're just quietly pacing the frontier...
They own their hardware. That vertical integration alone probably saves oodles because they can reconfigure to their needs as opposed to individually negotiating data centre plans. I can't imagine the complexity both OpenAI and Anthropic have to maintain for their deployments.
They may be buying it, but is there any indication they are using it for consumer-facing stuff? I would suspect given the scale there are many different things. I wish I knew more about standardization for cloud data center workloads though
It's not as smart as Claude Opus 5.5 High according to the AA benchmark. Looks like a big fat nothingburger so far, though it's possible that future fine-tuned checkpoints of the same pretrained model will do a lot better.
While that’s true, I have found Gemini models to be exclusively good for data extraction, and absolutely terrible at everything else.
I pay for lots of models because they’re good at different things: $20 a month each for Grok and GLM have easily paid for themselves by finding bugs that my main work models didn’t, but I’m yet to have any Gemini model find a real bug, and Gemini’s results for general work will sometimes border malicious compliance, when it’s not having a hissy fit about some imagined issue.
I checked price per AA task and yeah Argon vs Opus 5.5 High are practically neck and neck both on "intelligence" and cost per task. So if you aren't pushing higher on Opus (which I think can quickly become very expensive and I always treat Max and those like "benchmark settings"), I think this becomes more of a matter of which platform you like more or prefer for various reasons.
Honestly, I think this will be a trend in 2027 when all those models become "good enough" for elite coding and whatever. I predict they'll have to branch out more and build their platform to differentiate themselves from each other, maybe even in terms of branding and trust, marketing towards various demographies, youth vs elderly, students vs employees, etc.
I don't think the OP and your comments are mutually exclusive. If Anthropic usage is lower, and the OP considers it basically unlimited for their case, that just means that they would have virtually unlimited usage with other plans.
Sol 6.1 scores one point less than Gemini 4 on intelligence AND costs less than half ($0.72 vs $1.99) per task.
Additionally, if you are using OpenAI you have the option to pay a bit more and get Astra which - despite the benchmarks - does outperform Sol on some things.
Also, people are - rightly - very wary of Google's benchmaxxing tendencies. I think lots of people remember Gemini 3.0 (I think?) which benchmarked amazingly, but as soon as you used it would go off-track and needed constant babysitting if you wanted to use it for agentic work.
I wonder how they do this nerfing thing. One candidate is slightly decreasing the number of chain of thought tokens for each effort level. It must be something they do to meet increasing demand. Also the significant drop before a new release is because of reallocating the resources.
Methodology section in some of these benchmarks doesn’t say if they use subscription or API. API usage may not be nerfed as much as subscription.
They must be using the same lever to “pace the frontier”. All of the best effort models from different companies have similar scores. There is no standard definition of “max” effort level.
5 points off Opus 5.5 on AA, not a good release. Falling behind and not able to catchup. Ant probably has opus 6 in the works. Fumbled so hard on this, they should have owned AI.
That is considered a consumer-level surface so the prompt and features layered on top are more important than the model underneath. If you want the latest models you should use Antigravity, it's the "pro" interface.
I'm not sure Google can cut in when Claude and ChatGPT already got. I'm using both, but I'll keep track of whether Google can make it good enough for me to use also this Gemini, or cancel one of the two (Claude and ChaGPT) for it.
Companies out there are on google cloud or microsoft offerings and getting Gemini in their bundle, they aren't going through lawyers, etc, to provision from Anthropic or OpenAI just because they look a bit better on nerd benchmarks.
I’m guessing this is considered something like a C grade from Google if they are being honest with themselves.
After being nowhere near the frontier for a long time, they are pre announcing a model that ranks 3rd, roughly on par with models today that are cheaper.
Good for them to think about releasing to stay in the frontier game.
(I do think 3.7 flash was a solid release, so they are around the conversation. And their image and audio and live models are good)
anuragdaram | a day ago
krat0sprakhar | a day ago
https://blog.google/innovation-and-ai/models-and-research/ge...
1/5th the price of Astra and Fable
sroussey | 21 hours ago
anuragdaram | 4 hours ago
A_D_E_P_T | a day ago
thereitgoes456 | a day ago
asdfasgasdgasdg | a day ago
godbox | a day ago
yipinwong | a day ago
The price is enticing for cost per tasks, but let's see how it goes.
I have montly (cheapy) sub to gemini models and has been underwelming and lowered the tier.
dom96 | a day ago
godbox | a day ago
enraged_camel | a day ago
losvedir | a day ago
augment_me | a day ago
sourweasel | 22 hours ago
piyh | 23 hours ago
$10 per million output tokens isn't improving on frontier price?
godbox | 17 hours ago
netdur | 22 hours ago
dzhiurgis | 22 hours ago
ai-x | a day ago
So, like any optimal game theory move, they are better off not starting a price war
pooper | a day ago
ai-x | 21 hours ago
a) internal use b) embedding in their products c) stay abreast with capabilities
they can sit it out.
miohtama | 23 hours ago
blinding-streak | 21 hours ago
https://firstpagesage.com/reports/top-generative-ai-chatbots...
https://techcrunch.com/2026/06/16/chatgpts-market-share-slip...
gradus_ad | 22 hours ago
OpenAI and Anthropic are existential threats to Google and it will operate accordingly.
aliljet | a day ago
tomrod | a day ago
mkotlikov | 22 hours ago
tomrod | 22 hours ago
notatoad | 21 hours ago
the deal has a 30-day cancellation policy, and they raised a bunch of debt around the same time to fund their own datacenter expansion.
fragmede | 18 hours ago
genxy | 20 hours ago
largbae | 20 hours ago
zozbot234 | a day ago
mpyne | 23 hours ago
If it's smart enough to do the job then it won't matter that Opus is smarter. At the right price and performance, at least.
petesergeant | 14 hours ago
I pay for lots of models because they’re good at different things: $20 a month each for Grok and GLM have easily paid for themselves by finding bugs that my main work models didn’t, but I’m yet to have any Gemini model find a real bug, and Gemini’s results for general work will sometimes border malicious compliance, when it’s not having a hissy fit about some imagined issue.
jug | 11 hours ago
Honestly, I think this will be a trend in 2027 when all those models become "good enough" for elite coding and whatever. I predict they'll have to branch out more and build their platform to differentiate themselves from each other, maybe even in terms of branding and trust, marketing towards various demographies, youth vs elderly, students vs employees, etc.
aleqs | a day ago
Anthropic has some of the lowest usage per $ in general, not sure what you're taking about.
jjice | 23 hours ago
aleqs | 23 hours ago
8n4vidtmkvmk | 17 hours ago
It's all relative. Some people just can't use up their quotas with their normal usage.
aleqs | 16 hours ago
UltraSane | 22 hours ago
nl | 21 hours ago
Opus and Sol usage levels vs the API are currently roughly the same, but Opus 5.5 outperforms at low and medium effort levels.
sroussey | 21 hours ago
Melatonic | 13 hours ago
nl | 21 hours ago
Sol 6.1 scores one point less than Gemini 4 on intelligence AND costs less than half ($0.72 vs $1.99) per task.
Additionally, if you are using OpenAI you have the option to pay a bit more and get Astra which - despite the benchmarks - does outperform Sol on some things.
Also, people are - rightly - very wary of Google's benchmaxxing tendencies. I think lots of people remember Gemini 3.0 (I think?) which benchmarked amazingly, but as soon as you used it would go off-track and needed constant babysitting if you wanted to use it for agentic work.
re-thc | 13 hours ago
Via the API. The $200 OpenAI plan just got cut and most say general quotas got cut before that so for users on a plan the numbers might be different.
nl | 12 hours ago
scrollop | 16 hours ago
https://www.bridgebench.ai/nerf-bench
https://marginlab.ai/trackers/claude-code/ https://marginlab.ai/trackers/codex/
https://github.com/ninjahawk/livenerf
https://isitnerfed.org/
ozgung | 14 hours ago
Methodology section in some of these benchmarks doesn’t say if they use subscription or API. API usage may not be nerfed as much as subscription.
They must be using the same lever to “pace the frontier”. All of the best effort models from different companies have similar scores. There is no standard definition of “max” effort level.
algoth1 | a day ago
dang | a day ago
Gemini 4 Argon - https://news.ycombinator.com/item?id=49913571
jwpapi | 23 hours ago
small_model | 21 hours ago
mlmonkey | 21 hours ago
https://imgur.com/a/h96yg5t
This is on a $20/mo paid plan :cry:
radicality | 19 hours ago
brainwad | 16 hours ago
lhk931122 | 20 hours ago
epolanski | 14 hours ago
mchusma | 19 hours ago
After being nowhere near the frontier for a long time, they are pre announcing a model that ranks 3rd, roughly on par with models today that are cheaper.
Good for them to think about releasing to stay in the frontier game.
(I do think 3.7 flash was a solid release, so they are around the conversation. And their image and audio and live models are good)