Magic claims >10x more efficient pretraining, matches DeepSeek V4 Pro with 50x fewer FLOPs
Dr_Singularity · x · 2026-09-09
Startup Magic says its new pretraining recipe is over 10x more compute-efficient than leading open-weight models.
- Matches DeepSeek V4 Pro Base with 50x fewer FLOPs and $0.5M of GB200 compute
- Scaling to $4M produced a base model that beat all public open models on perplexity evals; estimated cost under DeepSeek's recipe: >$100M
- Magic is scaling toward trillion-parameter models and autonomous AI R&D
Related event: Magic Claims to Match DeepSeek V4 Pro Pretraining with 1/50 the Compute(11 posts)→
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