Magic vs Maywood

Magic AI Claims Frontier-Level Pretraining for Under $1M

Magic, an AI startup co-founded by Austrians Eric Steinberger and Sebastian De Ro, claims a major breakthrough in pretraining efficiency. Its new recipe reportedly matches DeepSeek V4 Pro's base model quality using 50x less compute, costing about $500,000 on Nvidia GB200 systems, and is over ten times more compute-efficient than leading open-weight models. Scaling to roughly $4 million, Magic says it outperforms all public base models on perplexity evaluations, comparing against DeepSeek V4 Pro, Kimi K2, and Nvidia's Nemotron 3 Ultra, while excluding closed models from Anthropic, Google, and OpenAI. The company has raised over $460 million, with a $320 million round valuing it at $1.5 billion, and partners with Google Cloud for tens of thousands of GB200 chips. Magic has not yet released a model, and all claims are self-reported.

• Magic claims its pretraining recipe matches DeepSeek V4 Pro's quality with 50x less compute, costing ~$0.5M on GB200, and is 10x more efficient than leading open models.
• Scaling the recipe to ~$4M, Magic says it beats all public base models on perplexity evaluations.
• Magic has raised over $460M, with a $320M round valuing it at $1.5B, and partners with Google Cloud for GB200 compute.

Maywood Integrates PitchBook's Private Market Intelligence into its AI Workflows

Maywood has partnered with PitchBook, the leading private capital market intelligence platform, to integrate its data into Maywood's AI harness, enabling Maverick to track private companies, identify key signals, and help teams make more informed deal decisions.

Maywood Publishes New Whitepaper: How to Do More Deals as an Investment Banker: A 400+ MD Study

A new whitepaper based on 432 conversations with dealmakers across 140 firms reveals how top managing directors build relationship coverage, source deal flow, and win mandates before a process exists.