Unverified50% confidenceFactExact time
Beam was pretrained on 23.8 trillion high-quality tokens.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedBeam adopts a Sparse Mixture-of-Experts (Sparse MoE) architecture with 52 layers, activating only 23 billion parameters at a time.65% similarUnverifiedBeam's VRAM requirement is close to that of a 501B-scale model, while its compute requirement is close to that of a 23B-scale model.60% similarUnverifiedBeam reaches frontier level on coding and agent tasks while using about 3-4 times fewer inference tokens than comparable open-source models.60% similarUnverifiedBeam's total parameter count is 501B, with 23B parameters activated per token (about 4.6% of the network is activated).60% similarUnverifiedBeam reaches 81.6% on SWEBench Verified (BF16).58% similar
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