Venture Capital Benchmark Q1 2026

US, Europe, and Latin America

VC Activity

Q1 2026 opened with a historic split between value and volume. Global deal count fell 27% compared to Q1 2025, continuing the trend of investors concentrating capital into fewer, larger bets across all regions. Yet total deal value told the opposite story, surging to $330.8B globally, with North America alone hitting $268.5B, more than 6x what it deployed in Q1 2025. North America captured 81% of global VC investment this Q1, a concentration level without precedent. Strip out the frontier lab megarounds and the underlying market remains cautious, but the headline numbers mark a structural shift in how and where capital is being deployed.

Early 2026 fundraising signals a cautious rebound after a difficult 2025. Global VC raised fell 41% in 2025 (from $217.8B in 2024 to $128.8B), continuing a multi-year contraction. Q1 2026 already shows $58.3B raised — 45% of the entire 2025 total in a single quarter. Whether this marks a genuine recovery or is concentrated in a handful of large platforms will become clearer as the year progresses.

Global VC exit value surged 124% QoQ in Q1 2026 to $413.4B, driven overwhelmingly by North American mega-exits. Exit count, however, dropped 20% QoQ to 700 deals globally, continuing a sustained decline across all regions. The gap between value and volume tells the same story as dealmaking: liquidity is returning, but it is highly concentrated and not yet broad-based.

Source: pitchbook

Q1 Trends

01

The rise of european mega-rounds

Q1 2026 has been defined by the emergence of "US-sized" mega-rounds in Europe. Investors are moving toward less saturated markets, leading to several record-breaking funding rounds:

Source: pitchbook

02

Agentic AI goes from pilot to production

Enterprise AI agents have crossed from experimentation to live workflows, and the revenue is following. Anthropic surpassed OpenAI in annualised revenue for the first time in Q1 2026, as enterprises turn agentic.

The open-source world accelerated the same shift, with new autonomous agent frameworks, like OpenClaw or Nanobot, becoming viral among developers, drawing endorsements from NVIDIA and prompting YCombinator to update its founding motto to “Make Something Agents Want”.

This is already playing out in our own portfolio: Simpliroute's ADA agents integrate directly with ERP, TMS, and WMS systems to autonomously resolve logistics incidents in real time. The new challenge is no longer convincing companies to try agents. It is scaling them without breaking things.

Source: Mayfield

03

Revenue is now an engineering problem

The fastest-growing companies in Q1 aren't hiring bigger sales teams, they're engineering their GTM as a system. AI handles prospecting, qualification, outreach, and expansion. Founders with an engineering mindset are outbuilding those with a sales mindset.

04

Bioscience is back, and investors mean it this time

After years behind SaaS, and then AI, bioscience is rebounding in Q1 2026. The focus has shifted from diagnostic tools to owning the continuous patient relationship. In a market where AI is now baseline, the true asset for the patient is the ongoing data stream, not the one-time diagnosis. Capital is re-pricing accordingly.

Portfolio companies Tiny Health, Tonic Easy Medical and Spike Technologies are all cases in point: ongoing patient data beats one-time diagnostics.

Source: labiotech

Predictions

Looking ahead

The IPO market gets its first real test

Q2 is when private market valuations meet public market reality. SpaceX is targeting a roadshow as early as June, with an unprecedented 30% retail allocation, while OpenAI and Anthropic are expected to file in H2. Tradingkey If SpaceX prices well, it accelerates the entire AI IPO pipeline. If it stumbles, it delays it. Q2 will tell us whether public markets can absorb what private markets have been building.

The models are commoditising

In Q1 2026 we saw the first clear signals that the intelligence layer is commoditising. Open-source models are closing the gap and local inference on consumer hardware is making access to capable AI nearly free. Heading into Q2 and beyond, we expect open-source to become the default starting point for most enterprise deployments.

Founder perspective

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