Which investors dominate AI hardware?

This blog post has been written by the person who has mapped the AI hardware investment market in a clean and beautiful presentation

The AI hardware investment landscape has become one of the most capital-intensive and strategically critical sectors in venture capital.

Leading venture firms deployed over $18 billion into AI hardware startups in 2024 alone, with Andreessen Horowitz and Sequoia Capital emerging as the dominant forces. Corporate venture arms like Intel Capital and Samsung Next have also become major players, often writing larger checks than traditional VCs.

And if you need to understand this market in 30 minutes with the latest information, you can download our quick market pitch.

Who are the top venture capital firms currently dominating investments in AI hardware, and what are the key startups they've backed?

Andreessen Horowitz leads the pack with approximately $2.5 billion deployed in 2024-H1 2025, backing powerhouses like Groq, SambaNova, Tenstorrent, Cerebras, and Lightmatter.

Sequoia Capital follows closely with $1.8 billion deployed, focusing on companies like Cerebras, CoreWeave, Mythic, and Graphcore. Their portfolio strategy emphasizes both training and inference accelerators with clear paths to revenue.

Intel Capital operates differently as a corporate venture arm, deploying around $500 million while leveraging strategic partnerships. They've backed SambaNova, Figure AI, Lightmatter, Anyscale, and Celestial AI, often providing more than just capital through manufacturing partnerships and technical expertise.

Samsung Next has emerged as a major force with $400 million deployed, particularly strong in photonics and ASICs. Their portfolio includes Tenstorrent, Lightmatter, Mythic, and Ayar Labs, with a focus on companies that complement Samsung's semiconductor ecosystem.

Looking for the latest market trends? We break them down in sharp, digestible presentations you can skim or share.

How much capital have these investors deployed into AI hardware startups in 2024 and so far in 2025?

The total global AI hardware VC funding reached approximately $18 billion in 2024, with the top 5 firms accounting for roughly 45% of this deployment, totaling around $8.1 billion.

For 2025 year-to-date through June, the major hardware rounds included CoreWeave's $1.1 billion Series D led by Coatue, Groq's $640 million Series D led by BlackRock, and Mythic's $700 million Series D led by Samsung Next. The estimated venture deployment for 2025 H1 sits at approximately $7 billion across infrastructure, accelerators, and interconnect companies.

Corporate venture arms have been particularly aggressive, with Intel Capital alone deploying over $500 million in 2024. This represents a significant shift from previous years where traditional VCs dominated hardware investments.

The deployment pace has accelerated dramatically compared to 2023, when total AI hardware funding was closer to $12 billion globally. This 50% year-over-year increase reflects the maturation of AI workloads and the desperate need for specialized silicon.

If you want fresh and clear data on this market, you can download our latest market pitch deck here

Which specific hardware startups have raised the largest rounds recently, and what are the details of those rounds?

CoreWeave topped the charts with a massive $1.1 billion Series D led by Coatue, with participation from Altimeter, Fidelity, and Magnetar, marking one of the largest infrastructure rounds in AI hardware history.

What types of AI hardware technologies or breakthroughs are attracting the most funding right now?

Domain-specific accelerators optimized for LLM inference are receiving the lion's share of funding, with companies like Groq and Tenstorrent leading this category.

Photonic interconnects represent the second-largest funding category, addressing data movement bottlenecks that traditional electrical interconnects can't solve. Ayar Labs and Lightmatter have raised significant rounds based on their optical I/O technologies that promise 10x improvements in bandwidth per watt.

Edge AI ASICs for low-power inference in embedded and IoT applications are attracting substantial investment, particularly from companies like Mythic and Untether AI that focus on energy-efficient architectures. These chips target applications where power consumption and thermal constraints are critical.

AI-native cloud services built around GPU infrastructure represent another major funding category, with CoreWeave and Cerebras building specialized data centers optimized for AI workloads rather than general-purpose computing.

Curious about how money is made in this sector? Explore the most profitable business models in our sleek decks.

Which countries or regions are attracting the majority of AI hardware investment activity?

North America dominates with approximately 65% of global AI hardware funding, concentrated primarily in Silicon Valley, Boston, and Austin.

The Silicon Valley ecosystem remains unparalleled for AI hardware startups, benefiting from proximity to major tech companies, established semiconductor talent, and deep venture capital networks. Boston has emerged as a strong secondary hub, particularly for photonics and advanced materials companies.

Europe accounts for roughly 15% of funding, with the UK leading through companies like Graphcore, followed by Germany and the Netherlands. The EU's strategic autonomy initiatives have increased local funding for AI chip companies, though they still lag significantly behind US investment levels.

Asia represents about 20% of funding, split between China's domestic venture arms (Alibaba, Huawei), South Korea's Samsung Next ecosystem, and Japan's corporate investors like Sony and NTT. However, US export restrictions have complicated cross-border investments in this sector.

What roles are major tech giants like NVIDIA, Intel, AMD, Microsoft, Amazon, or Google playing as direct investors or strategic partners in the AI hardware space?

NVIDIA operates as both the primary GPU provider and a strategic investor through Nvidia GPU Ventures, while also serving as a compute-as-a-service partner for many startups testing their architectures.

If you want to build or invest on this market, you can download our latest market pitch deck here

Are there any notable corporate venture arms that are particularly active in backing hardware startups?

Intel Capital stands out with over $13 billion deployed across 1,550 companies historically, recently spinning off as a standalone entity in January 2025 with increased autonomy for investment decisions.

Samsung Next has become exceptionally active in AI hardware, serving as the key backer of Mythic's $700 million round, Tenstorrent's $693 million round, and Lightmatter's growth funding. Their focus on photonics and ASICs aligns perfectly with Samsung's semiconductor roadmap.

GV (Google Ventures) leverages Google Cloud synergies while backing companies like Enfabrica, Groq, Lightmatter, and Tenstorrent. Their investments often come with implicit partnerships for cloud deployment and customer introductions.

Other notable corporate venture arms include Qualcomm Ventures (focused on edge AI and 5G integration), Sony Innovation Fund (imaging and sensor applications), and Bosch Ventures (automotive and industrial AI applications). These firms often provide more than capital, offering manufacturing partnerships, customer relationships, and technical expertise.

What are the typical deal terms or expectations from leading investors in this space?

Check sizes vary dramatically by stage, with early-stage rounds typically ranging from $5-30 million and growth-stage rounds reaching $100-700 million.

Equity stakes for lead investors typically range from 10-25% in Series A rounds, dropping to less than 10% in late-stage rounds as valuations climb into the billions. Board rights are standard for lead investors, with pro-rata rights becoming increasingly important as rounds grow larger.

Milestone-based tranches have become common, particularly for hardware companies where development risks are high. These tranches are typically tied to specific product tape-outs, performance benchmarks, or time-to-market achievements.

Liquidation preferences are usually 1x non-participating preferred, though some growth-stage investors demand higher multiples or participating preferred structures. Anti-dilution provisions are standard, with weighted average broad-based being the most common structure.

Planning your next move in this new space? Start with a clean visual breakdown of market size, models, and momentum.

Which early-stage startups in 2024–2025 are considered rising stars with significant traction or promising technologies?

Rebellions (Sohu) has gained attention with their edge inference ASIC, raising a $25 million seed round and establishing partnerships with FPGA manufacturers for rapid prototyping and deployment.

If you need to-the-point data on this market, you can download our latest market pitch deck here

What trends are emerging in public or late-stage funding for AI hardware companies?

IPO pipelines are building with companies like Graphcore, SambaNova, and Cerebras exploring SPAC and direct listing options for 2026, though market conditions remain challenging for hardware IPOs.

M&A activity has intensified as large players like Intel, AMD, and Qualcomm acquire startups primarily for their intellectual property rather than their products. Intel's $2 billion acquisition of Habana Labs set the precedent for these strategic IP acquisitions.

Sovereign wealth funds from the Middle East and Singapore have become major co-investors in megadeals, with funds like Mubadala and Temasek providing patient capital for long development cycles. These funds often have strategic interests beyond financial returns.

Late-stage investors are increasingly demanding clearer paths to profitability and near-term revenue streams, moving away from pure technology bets toward companies with established licensing or cloud-pay business models.

How are investors evaluating R&D-heavy companies in this field?

Working silicon tape-out has become the minimum viable milestone for serious institutional investment, with investors demanding proof that the architecture actually works in silicon rather than just simulation.

Performance parity or superiority compared to incumbent solutions (typically NVIDIA GPUs) serves as the key technical benchmark, with investors focusing on specific metrics like TOPS per watt, memory bandwidth, and total cost of ownership.

Patent portfolio strength and architectural differentiation have become critical evaluation criteria, particularly as the industry faces increasing litigation and IP blocking strategies from incumbents.

Partnership validation through hyperscaler pilots or foundry alliances (particularly with TSMC or GlobalFoundries) provides crucial third-party validation of both technical merit and commercial viability. Clear product roadmaps spanning training to inference to edge deployment demonstrate long-term strategic thinking that investors value highly.

Not sure where the investment opportunities are? See what's emerging and where the smart money is going.

Based on 2024–2025 data, what investment trends or shifts should be expected in 2026 for those entering this market now?

Deeper specialization toward AI-native hardware for specific verticals like healthcare imaging and autonomous vehicle perception will attract significant funding as general-purpose AI accelerators become commoditized.

The shift toward inference-focused funding will accelerate, with the majority of new investment pivoting away from training accelerators toward inference and edge deployment solutions where profit margins remain higher.

Cross-border funding will continue growing as non-U.S. limited partners allocate more capital to U.S. megafunds, with Andreessen Horowitz targeting a $20 billion fund for 2026. This capital influx will drive larger round sizes but also higher valuation expectations.

Consolidation through M&A will intensify as tech giants acquire emerging IP before it becomes competitive threats, creating exit opportunities for early investors but fewer independent players in the market.

Capital efficiency demands will increase dramatically, with investors requiring clearer paths to profitability and revenue generation rather than pure technology development, favoring companies with licensing or cloud-service business models over traditional hardware sales.

Conclusion

Sources

1. PE Insights - Andreessen Horowitz AI Mega Fund
2. Feed the AI - A16Z AI Startups Portfolio
3. AIM Media House - Top AI Startup Funding 2024
4. Reddit - Sequoia Capital AI Investment Analysis
5. Wikipedia - Intel Capital
6. LinkedIn - AI Startups Analysis
7. Yole Group - Hottest AI Hardware Companies 2025
8. Scale Capital - Generative AI Landscape Q3 2024
9. Lazard - AI Infrastructure Report
10. Reuters - Andreessen Horowitz $20B Megafund