Comment by onlyrealcuzzo
1 day ago
This appears to be larger than DeepSeek v4.1 Flash, more expensive to run, and worse on every measured metric.
Am I missing something?
1 day ago
This appears to be larger than DeepSeek v4.1 Flash, more expensive to run, and worse on every measured metric.
Am I missing something?
> Am I missing something?
It's pretty clear from their framing ("Beam advances the Western open-weight frontier") that one of their main selling points is not being a Chinese lab.
I can't imagine that mattering to many individuals, but I guess someone out there has a government contract that forbids the use of foreign models
Reflection raised on the idea of creating the "American Deepseek Project"
Who's funding this?
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Multiple independent approaches are cool and all but fully open source model training (datasets, pipeline, checkpoints) should be taking advantage of being open and share runs/budget between different entities.
We're still at the stage where every new entrant is welcome in my opinion. Doesn't need to be record-breaking upon initial release.
It depends! If a startup is entering with a large model to face other larger models, it must be better at least in 1 meaningful dimension.
500B params performing worse than other OSS of the same size is pretty meaningless if no one will use it.
Look at meta, while they went from open to closed, they got better as time went on
I mean, the obvious way it's better than the Chinese open-weight models is literally the fact that it's not Chinese and is therefore less likely to be banned or restricted. Chinese models cannot be used on certain government systems already in the US, and regulators are actively considering expanding these restrictions more generally (such as adding it to the Entity List).
I disagree. Sure let them play and see if they can improve. But this model has more compute and more training data than the predecessors it fails to surpass. That only means their training regime is inferior if their predecessors did so much more with so much less. That inferiority should not be encouraged.
You don't just magically do better than everyone else on every metric on your first go at something. Doing worse than others and refining is how pretty much everything works.
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The reality is they trained a model and it looks worse on benchmarks than Qwen or GLM. I don’t see how sharing the weights hurts anyone? Even when Llama 4 came out and it was a dumpster fire, it didn’t affect me personally.
> That only means their training regime is inferior if their predecessors did so much more with so much less
Hard to imagine how that wouldn’t be the case. They probably missed the boat on distilling Claude (or their lawyers said no), they probably didn’t hire an army of math PhDs to write reasoning traces, they don’t have millions of DAUs in a coding agent to train from, and they probably have less money, less experience, fewer top tier researchers, and fewer resources for experiments. They are an underdog without a doubt.
None of that means they shouldn’t release their model.
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I wonder if that's an indication that they are not distilling which limits how good they can get.
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Reflection is explicitly marketed as the 'US' DeepSeek
seems like they are aiming to provide both inference and RLaaS for american companies and western govts. even if they never fully beat deepseek if they get close enough the fact that they're American will help them close deals
Apparently there is more to making good models than copying everything on the internet.
deepseek is from the evil east, this is from the virtuous west
12 yards long, 2 lanes wide, 65 tons of American Pride! Canyonero! Canyonero!
Yes it's (hopefully) not distilled from every single major American provider.
new entrant in this weight class, US lab.
Beam goes brrrr