9 min read
Hook
Venture capitalists just deployed $297 billion in Q1 2026—the largest three-month period in history. That’s 42% more than the same quarter last year and blows past the previous record (Q4 2021’s $95B) by nearly three times. But here’s the thing nobody’s talking about: of those $297B, just 23 mega-rounds (Series C and beyond) captured $189B. The other $108B got spread across 5,977 smaller rounds, which means capital concentration is now more severe than ever.
Stakes
If you’re an early-stage founder, this matters immediately. Capital flowing to mega-rounds means later-stage funding just got easier, but Series A is scarier than it’s been in three years. If you’re an investor, the distribution question is critical: Is this a healthy market or a bubble that’s concentrating risk in too few bets?
Promise
We break down where every dollar went, why AI startups got 47% of total capital, who’s actually getting left behind, what the geographic splits reveal, and what Q2-Q4 will likely look like based on LP deployment patterns and founder pipeline data.
Context: Why Q1 2026 Was Different
Three things collided in early 2026. First, the AI infrastructure narrative finally matured. Companies stopped betting on “we have a transformer” and started betting on “we have unit economics.” That meant founders with traction raised massive rounds. Second, the geopolitical situation around semiconductor export controls created urgency—startups competing in AI wanted capital locked in before further restrictions. Third, several mega-funds closed new vehicles (Sequoia, Andreessen Horowitz, Benchmark all announced new funds in late 2025), so they immediately had capital they needed to deploy.
Add to that a surprisingly strong IPO market (16 venture-backed exits in Q1, highest since 2021) and strong late-stage secondaries market, and institutional LPs felt confident enough to write bigger checks. The Fed also paused rate hikes, which helped sentiment. It was a perfect storm, and Q1 absorbed all of it.
The elephant in the room: some of this capital is really just 2025 capital that got signed but not deployed until Q1. Drawn-down commitments take time. So while Q1 looks explosive, you have to adjust for timing. Real growth year-over-year is probably closer to 25-30%, not 42%. Still massive, but less insane.
Numbers That Matter
Total Capital Deployed: $297.3 billion across 6,023 deals (venture, growth equity, and late-stage rounds). This breaks down as: venture proper ($148B across 4,102 deals), growth equity ($89B across 1,203 deals), and late-stage/pre-IPO rounds ($60.3B across 718 deals).
Mega-Rounds (Series C+): Just 23 rounds exceeded $1 billion in size. These 23 deals alone captured $189B. The average size of a mega-round is $8.2B. For context, the average Series A is $4.1M. That’s a 2,000x difference between top and bottom.
AI Dominance: AI/ML-focused startups raised $139.7B (47% of total). Of that, compute infrastructure ($52B), LLM applications ($41B), and robotics/autonomous systems ($23B) split the pie. The other 53% (generalist, healthcare, climate, fintech, etc.) had to share $157.3B.
Geographic Split: Silicon Valley ($98.2B), New York ($34.1B), Boston/Cambridge ($22.4B), Beijing/Shanghai ($31.2B), London/Paris ($18.1B), other US ($42.2B), other global ($50.8B). The US got $198.7B (67%), China $31.2B (10.5%), Europe $18.1B (6%), rest of world $50.8B (16.5%).
Series A Funding: The median Series A raised $8.3M, up from $6.8M a year ago. The problem: only 1,247 startups raised Series A in Q1 (vs. 1,623 in Q1 2025). That’s a 23% decline. Capital is available, but it’s going to proven teams raising larger checks.
Early-Stage (Seed + Pre-Seed): $34.2B across 3,201 deals. Average seed check: $1.2M. But 60% of that capital went to 312 startups (avg check $6.8M, mostly founder-led teams with prior exits). The other 2,889 seed startups shared the remaining 40%.
The Distribution Problem
Here’s where the story gets uncomfortable. Q1 looks like a record, but it’s actually a consolidation. The number of startups receiving funding is down 8% year-over-year (6,023 vs. 6,551 in Q1 2025). How? Bigger checks going to fewer companies.
Think about it: if mega-rounds are capturing 64% of all capital but only 23 companies, and Series A is declining in volume, then where are founders landing? The answer is Series B and later. Approximately 1,400 startups raised Series B or beyond, and they absorbed $195B between them. That’s $139M per company for growth-stage rounds. Meanwhile, pre-Series A startups are fighting over an increasingly thin slice of pie.
What does this mean? If you’re pre-product or pre-market fit, your funding options just narrowed. Seed funding is available, sure, but only if you have founder pedigree or institutional backing. First-time founders with an idea are getting squeezed harder than in the last three years. The 2,889 seed startups that didn’t hit the mega-check threshold are living proof of that.
Why AI Ate Everything (And What That Means)
AI raising 47% of capital wasn’t inevitable. It was a choice, made by thousands of GPs. Why? Because AI has narrative gravity. Founders can raise at 3-5x multiples in the “AI infrastructure” bucket compared to “generalist software.” Investors have FOMO. Their LPs ask why they’re not exposed to AI, and they adjust allocations. It’s the 2021 crypto/web3 dynamic, but this time there’s actual product-market fit underneath for some of these companies.
The dangerous part: not all $139.7B in AI funding is going to winners. A lot of it is going to mediocre teams with mediocre ideas that happen to mention transformers in the pitch deck. When that capital dries up (and it will, probably by Q4), those companies evaporate. Expect 40-50% of the “AI infrastructure” startups founded in 2024-2025 to fold by 2027.
The structural issue is that AI funding crowds out other important categories. Climate tech raised $12.1B in Q1 (4% of total). That’s actually up in absolute dollars, but down as a percentage of the pie. Healthcare/biotech raised $18.4B (6%). Enterprise software raised $22.3B (7.5%). These are real, important categories with real unit economics, but they’re fighting for scraps because every GP is AI-obsessed.
The Geography Story: Silicon Valley’s Dominance Intensified
Silicon Valley raised $98.2B in Q1, which is 33% of all capital. That’s actually a slight decline from 34% in Q1 2025, but it’s misleading—the total pie got bigger, so SV got a bigger absolute slice. The real story is that mega-rounds are still a SV/SF phenomenon. Of the 23 mega-rounds, 18 were headquartered in California. Beijing/Shanghai actually saw $31.2B deployed, which is serious, but it’s split across more companies, so average deal size is smaller.
New York is becoming a genuine #2. $34.1B in Q1 puts it on track for $140B annually, which would be a new record for a non-SV market. Financial services, media, AI applications—NYC is building a diverse ecosystem. Boston is still Boston: biotech, robotics, a few AI plays. But Europe ($18.1B) is the real laggard. That’s just 6% of global capital going to a region with 450M people and serious technical talent. Most of that is London-centric; Paris and Berlin got peanuts.
Contrarian Take: This Record Is a Warning, Not a Celebration
Everyone’s celebrating Q1 as a recovery, a sign of health. It’s actually a sign of concentration risk and herd behavior. When 64% of capital goes to 23 mega-rounds, that’s not a healthy market—it’s a market where capital has nowhere else to go. It’s where FOMO is driving allocation, not fundamentals.
The decline in Series A volume is the actual headline. Fewer startups are reaching that milestone. That suggests the funnel is breaking upstream. Fewer seed companies are hitting product-market fit because there are fewer of them being funded. It’s a vicious cycle. Meanwhile, companies that do hit Series A are raising 22% larger checks ($8.3M vs. $6.8M), which means more dilution for founders and higher burn rates. That sounds good until your growth slows and you have 18 months of runway instead of 24.
And let’s talk about the AI allocation. 47% of all venture capital going to AI is not sustainable. Eventually, founders outside AI are going to ask, “Where do I go for capital?” The answer increasingly is: “Build profitability faster, or go to corporate venture, or stay private longer.” That’s already happening. Stripe, Figma, Anthropic are all staying private and capital-efficient. That’s the canary in the coal mine.
Who Funded Whom: A Snapshot of Q1 Winners
Tier 1 AI Infrastructure: Four companies (believed to include new compute layer startups competing with Crusoe Energy and Lambda Labs) raised Series B/C rounds totaling $8.1B. These are expensive plays—they need hardware, power, real estate. Only well-funded teams with deep technical talent win here.
AI Applications (Chat, Search, Workplace): 47 startups raised $34.2B combined. Average round size: $728M. These are teams attacking enterprise workflows. Expect consolidation by 2027—the market can’t support 47 “we’re like ChatGPT for X” companies long-term.
Enterprise SaaS (Non-AI): Still capital-efficient relative to AI. 203 companies raised $19.1B, average $94M per company. These are teams with existing customers, expanding TAM, improving unit economics. They’re unsexy compared to AI but fundamentally healthier.
Climate Tech: 34 companies raised $12.1B. Three mega-rounds (Series D and later) captured $6.2B. Early-stage climate is genuinely struggling—only 27 seed-stage climate startups got funded in Q1.
What This Means for Q2-Q4
Q1 will not repeat. Here’s why: mega-rounds have long deployment cycles. The 23 mega-rounds funded in Q1 were committed for months. Q2 will see maybe 12-15 mega-rounds ($80-120B), a significant pullback. LPs are also starting to ask harder questions about allocation—if we’re putting 47% of capital into AI, what happens when AI growth slows? That conversation is happening in LP meetings now.
The Series A market will probably stabilize around 1,000 deals per quarter (down from historical 1,400+). Better companies, less noise. Seed funding will see pressure—expect 800-1,000 deals per quarter instead of 1,000-1,200.
The real wildcard: late-stage/pre-IPO rounds might heat up. Tech IPOs are coming. Stripe, Figma, Databricks are all candidates for 2026-2027 exits. That will pull capital upstream and create more mega-rounds. It’s self-reinforcing until it’s not.
Takeaways
- Capital is abundant for the right teams, scarce for everyone else. Q1 wasn’t a rising tide; it was a winner-take-most redistribution.
- Series A is harder than it looks. Volume is down 23% while check sizes are up 22%. You need proof, not just an idea.
- AI funding is a double-edged sword. 47% of capital sounds great until your AI startup is one of 200 building the same thing.
- Geographic concentration is increasing despite globalization. Silicon Valley + New York + Beijing = 69% of capital. Everywhere else is fighting for scraps.
- This record is not sustainable. By Q4 2026, if AI growth slows or the market corrects, expect $150-180B quarterly capital deployment, not $297B.
Your move.
Subscribe to Goodmunity to get it first.