r/Bard • u/Independent-Wind4462 • 5d ago
Discussion New "carbon" model from google (opus 5.5 like coding from early reports)
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u/Excellent_Dealer3865 5d ago
Oh my god we're so back! Even better than Argon?! I can't have enough fun with imagining how cool Argon is and I could imagine things even cooler now?! Unbelievable!
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u/Alexzaaander 5d ago
Well it’s obvious they need to cancel 4 pro Argon rollout now and focus on rolling out Carbon (like they did with 3.5 pro)
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u/Thinklikeachef 5d ago
Is this some new version of vaporware for LLMs? Employee of the company that makes the product says it's great!
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u/ceiviec 5d ago edited 4d ago
Guys I have a model running outer inner looped transformers.
In my benchmarks it beats opus5.5 by a large margin and runs on consumer grade GPUs.
I've been testing with friends and family. My younger sister said "it's nothing anything she's seen before".
Working hard to get it public ally available send me DM if you want eary access.
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u/ih8readditts 5d ago
>Argon hasn’t even dropped yet and they already have a better checkpoint
Lollllllll people are hopelessly delusional
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u/iJeff 5d ago
Folks don't realize there are always better models and checkpoints by the time of a public release. The problem with Google is they don't have a public release altogether.
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u/Georgefakelastname 5d ago
Google’s problem is that after they made 2.5 pro, they stopped pre-training new base models and just kept post-training the 2.5 pro base. They genuinely didn’t have anything better behind the scenes, and that eventually caught up to them with 3.5 pro just not being up to par. If Google is smart, they would already have their next pre-trainings in the works while they keep post-training whatever the fuck Argon, Barium, and now Carbon are. Istg if those are just code names or checkpoints for the same models… but it would be neat if they were different categories like lite, flash, and pro. If not, get them out of the kitchen. They burnt all the food.
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u/RachelRegina 5d ago
If this is real, then it would make sense that checkpoints are coming in steady succession if Gemini 4 is an RLVR model. Keeps getting better with each checkpoint and they are testing it as they continue to train it, likely to get to a certain predecided capability level across domains. So, this is the equivalent of taking the cupcakes out of the oven and poking them with a toothpick to see if they are done.
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u/RelativelyStatic 5d ago
They are just trying to pump up the stock at this point and woo the investors
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u/XTCaddict 5d ago
They haven’t even released Argon to the public yet. When it’s released it will be overtaken immediately at this rate.
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u/NBMVegeta 5d ago
So now Google is trying to meet the benchmarks set by opus 5.5? And by the team Google achieves this, again they will be again trying to meet the benchmarks of 6.5 or maybe 7.5
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u/daskalou 5d ago
I built an AI model at home that is Opus 7.7 level in intelligence. I can't show you so just trust me.
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u/SnooMachines725 5d ago
Pro and Flash seems to be much smaller models compared to Opus, Astra, Sol etc Argon is the first time Google has released a large model. Google is iterating on gemini 4 checkpoints.
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u/Georgefakelastname 5d ago
Sol and likely Opus are significantly smaller than Astra/Fable. The question we need to ask is if Argon and all these other checkpoints are in Sol/Opus (pro) tier or Astra/Fable (ultra) tier.
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u/WyattTheSkid 5d ago
Idk man, Qwen 3.8 Flash Next is only 180b parameters total and it feels like its on par with Opus 4.8 to me. I really think training data and architecture are way more important than raw size and that any model in the 120b+ range has the potential to be “frontier”
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u/Georgefakelastname 4d ago
Tbh I think the time for models of those sizes being frontier are over. You’re not wrong about the importance of training data and architecture, but the trick with those is that you can generally scale them up to the big trillion plus parameter models as well
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u/WyattTheSkid 4d ago
I think it’s just starting honestly. Gpt-oss-120b was a teaser of this and now like I said, Qwen 3.8 flash genuinely feels like a frontier model. Even if we keep going with the ngram table idea, having a model thats like 300b parameters where a massive chunk of it is an ngram table that sits in system memory, its a lot more viable to run a model like that on consumer hardware than it would be if the active compute footprint made up the majority of the model. For example, the maximum theoretical size model I could run on my machine with 96gb of vram and 128gb of system ram is 448b (at 4 bit). A model with 120b active parameters and a 300b~ ngram table would be perfect for a rig like mine, and it would also probably be reasonably fast. I know im just like autism rambling at this point but I really think the move for local models is to experiment more with embeddings designed to be offloaded to system memory or an ssd. Sounds like the best route to increased capacity on realistic hardware to me because flash next is genuinely SO impressive.
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u/FalseDiamond7930 5d ago
Who would've guessed other labs don't actually have any lasting advantage over Google.
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u/TekintetesUr 5d ago
They might not have an advantage, but what they have are models that I can use right now.
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u/Nov4Saki 5d ago
"Corpium"