Contrary to the belief that smaller VC funds generate higher multiples, a16z's data shows their larger funds can outperform. This is driven by the massive expansion of private markets, where significant value is now created in later growth stages (Series C and beyond).

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Mega-funds can justify paying "stupid prices" at the seed stage because they aren't underwriting a seed-stage return. Instead, they are buying an option on the next, much larger round where they'll deploy real capital. This allows them to outbid smaller funds who need to generate returns from the initial investment itself.

Venture-backed private companies represent a massive, $5 trillion market cap, exceeding half the value of the 'Magnificent Seven' public tech stocks. This scale signifies that private markets are now a mature, institutional asset class, not a small corner of finance.

Applying Conway's Law to venture, a firm's strategy is dictated by its fund size and team structure. A $7B fund must participate in mega-rounds to deploy capital effectively, while a smaller fund like Benchmark is structured to pursue astronomical money-on-money returns from earlier stages, making mega-deals strategically illogical.

A core part of a16z's growth fund strategy is to invest in companies the firm's early-stage team passed on. This acts as an internal "fix the mistake fund," providing a structured way to correct errors of omission and get a second chance at breakout companies.

VC funds between $50M and a few hundred million can be a 'dead zone' for general partners. They are too large to benefit from the quick-carry potential of small funds but too small to generate significant management fees like mega-funds, making the personal economics challenging for managers.

The primary risk to a VC fund's performance isn't its absolute size but rather a dramatic increase (e.g., doubling) from one fund to the next. This forces firms to change their strategy and write larger checks than their conviction muscle is built for.

A smaller fund size enables investments in seemingly niche but potentially lucrative sectors, such as software for dental labs. A larger fund would have to pass on such a deal, not because the founder is weak, but because the potential exit isn't large enough to satisfy their fund return model.

True alpha in venture capital is found at the extremes. It's either in being a "market maker" at the earliest stages by shaping a raw idea, or by writing massive, late-stage checks where few can compete. The competitive, crowded middle-stages offer less opportunity for outsized returns.

David George of Andreessen Horowitz reveals that contrary to the belief that smaller funds yield higher multiples, a16z's best-performing fund is a $1B vehicle. This success is driven by capturing enough ownership in massive winners like Databricks and Coinbase, demonstrating that fund size can be an advantage in today's market where value creation extends into later private stages.

AI startups' explosive growth ($1M to $100M ARR in 2 years) will make venture's power law even more extreme. LPs may need a new evaluation model, underwriting VCs across "bundles of three funds" where they expect two modest performers (e.g., 1.5x) and one massive outlier (10x) to drive overall returns.