> Beam is a sparse Mixture-of-Experts model with 501 billion total parameters, 23 billion active, built for coding, reasoning, and agentic workloads.

> Beam’s capabilities come from major investments in both pretraining and reinforcement learning (RL). We pretrained the model on 23.8 trillion diverse, curated, high-quality tokens from the web and proprietary licensed datasets, matching or outperforming available similar-sized open base models. In parallel, we developed the algorithms, training environments, and infrastructure needed to sustain high-compute RL at exceptional scale. Our high-compute RL run generated over 100 million rollouts on 10.5K NVIDIA GB300 GPUs over 4 weeks of training.

Early access, no weights no tech details, just a sign up here for info

▲

wronglebowski 4 hours ago | parent | next [-]

I'm all for more open models, but talk is cheap and this is a rather pointless announcement without anything backing it up. Publish your weights and HF repo or shut up IMO.

▲

zelphirkalt 4 hours ago | parent | prev | next [-]

And also a "proprietary data set" hahaha... Probably just means they don't want to show it, and it is data, that either they shouldn't have, or that there is nothing special about their training data and it is just meant to sound like there is some secret ingredient, while there is none.

	▲	janalsncm 3 hours ago \| parent \| next [-]
		Not sharing the data is pretty standard because 1) it tends to get the lawyers involved and 2) good data is critical for getting good results. Imo you can get better results with great data and generic modeling techniques than with incredible modeling techniques and crappy data. Because if you have crappy data, you won’t even know if your model is good because your evals will also be bad. This is why Anthropic is throwing a fit about the Chinese distillation “attacks”. Clean reasoning traces are gold.
	▲	mlmonkey 2 hours ago \| parent \| prev \| next [-]
		Data has copyright issues, so one can't share it generally without getting permissions from all of the copyright holders. The data is not theirs to share, anyways. The derived (learned) weights are a different matter.
	▲	vanuatu 3 hours ago \| parent \| prev [-]
		this is very normal for frontier lab companies. you need good data either synthetic or labelled (all the chinese open source models have their own armies of data labelers)

▲

Loquebantur 3 hours ago | parent | prev [-]

> Beam is undergoing final red-teaming and evaluations. You can sign up here for early access to the model.

> We will release the weights, technical report, model card, and developer artifacts later this month.