What is the latest update in the AI chip market?

The AI chip market is moving fast, and Q1 2026 brought some of the biggest product launches, partnerships, and financial results in the industry's short history.

This blog post is our latest quarterly update, and we constantly refresh it so you always have the most current picture of what is happening.

And if you want to better understand this new industry, you can download our pitch covering the AI chip market.

Summary table of the most important updates in the AI chip market

We define the AI chip market as data-center accelerators whose primary purpose is to run AI workloads (training and inference).

We include GPUs, TPUs, and other AI accelerators/ASICs sold for deployment in servers used to train or serve machine-learning models.

We exclude general-purpose CPUs, networking and memory components, and endpoint/edge chips in phones, PCs, cars, and IoT devices.

You can also get all the latest market news for the month here.

News	Category	Date	Source
NVIDIA launched Rubin, its next-generation AI supercomputer platform, pulling the roadmap forward again	Product launches	Jan 5, 2026	NVIDIA
NVIDIA posted record quarterly revenue of $68.1 billion with $62.3 billion from data centers	Financial results	Feb 25, 2026	NVIDIA
AMD and Meta announced a multi-year deal to deploy up to 6 gigawatts of AMD GPUs	Partnerships	Feb 24, 2026	AMD
NVIDIA described Vera Rubin as a full AI factory blueprint with seven chips in production	New tech	Mar 16, 2026	NVIDIA
Broadcom reported AI semiconductor revenue of $8.4 billion, up 106% year over year	Financial results	Mar 4, 2026	Broadcom
Microsoft unveiled Maia 200, a 3nm inference accelerator with 216GB of HBM3e	Product launches	Jan 26, 2026	Microsoft
AMD reported record Q4 revenue of $10.3 billion and full-year revenue of $34.6 billion	Financial results	Feb 3, 2026	AMD
SambaNova launched SN50, partnered with Intel, and raised over $350 million	Fundraisings	Feb 24, 2026	SambaNova
AMD and Nutanix formed a strategic partnership with a $250 million commitment	Strategic investments	Feb 25, 2026	AMD
U.S. Commerce Department revised export rules, reopening a path for some AI chip sales to China	Regulations	Jan 13, 2026	BIS
Oracle deployed rack-scale NVIDIA GB200 NVL72 systems with dedicated cloud APIs	Customer wins	Jan 28, 2026	Oracle
Marvell reported record revenue and said AI demand is driving all-time-high design wins	Financial results	Mar 5, 2026	Marvell

How is the AI chip market doing now?

How do we define the AI chip market?

We define the AI chip market as data-center accelerators whose primary purpose is to run AI workloads (training and inference).

We include GPUs, TPUs, and other AI accelerators/ASICs sold for deployment in servers used to train or serve machine-learning models.

We exclude general-purpose CPUs, networking and memory components, and endpoint/edge chips in phones, PCs, cars, and IoT devices.

This is also the definition we use in our report covering the AI chip market.

How big is the AI chip market in 2026?

We estimate the AI chip market will reach approximately $240 billion in 2026, growing about 16% from the $207 billion level in 2025.

This is not a random guess, if you want to know how we have come up with this estimate, you can read our AI chip market size analysis here.

To put that number in perspective, the AI chip market in 2026 is roughly the same size as the entire global automotive semiconductor market, which sits at around $250 billion.

The AI chip market is moderately mature (55/100), intensely competitive (80/100), and not very fragmented (35/100), meaning revenue is concentrated among a small number of large players led by NVIDIA, with hyperscaler custom silicon growing fast behind them.

How fast will the AI chip market grow in the future?

We estimate the AI chip market will grow at approximately 12% CAGR from 2026 through 2036, driven mainly by the expansion of inference workloads across enterprise and consumer applications.

At that pace, the AI chip market should reach roughly $377 billion by 2030 and approximately $747 billion by 2036, which would be more than three times its current size.

That growth trajectory looks a lot like what happened with cloud infrastructure spending over the past decade, but with extra constraints from power availability and capital expenditure limits that could slow things down.

What does current funding activity look like in the AI chip market?

Our team, who continually updates our AI chip market pitch deck, is keeping a close eye on the market and tracking key signals.

One of those signals is fundraising activity across startups. Each month, we refresh this page with a list of startups of the AI chip market that have raised funding, and we also publish a quarterly analysis here.

Is funding momentum accelerating or cooling in the AI chip market these days?

Q1 2026 saw at least two major AI chip funding rounds totaling over $580 million, with SambaNova raising $350 million and Positron raising $230 million, showing that investor appetite for AI silicon alternatives remains strong.

Compared to the same period a year ago, the average deal size in the AI chip market has grown significantly, as both Q1 2026 rounds were well above the $100 million mark, reflecting a shift toward fewer but much larger bets on companies with real chips and customers.

The pattern in Q1 2026 is clear: investors are concentrating capital into later-stage companies that have already proven they can ship silicon, rather than spreading smaller checks across early-stage ideas.

Which categories and business models are attracting capital in the AI chip market?

These categories and business models of the AI chip market are receiving important fundraising currently:

• Inference-focused AI accelerators: Positron raised $230 million to build dedicated inference hardware, and SambaNova raised $350 million for its agentic AI inference chip, showing that inference is where the capital is flowing.
• Full-stack AI chip companies with manufacturing partnerships: SambaNova combined its chip launch with an Intel collaboration, showing investors value companies that can pair custom silicon with established supply chains.

The message from Q1 2026 funding is simple: investors in the AI chip market are betting that inference, not training, is the next big revenue opportunity.

Who's writing the most checks in the AI chip market?

These investors are being very active when it comes to fundraising in the AI chip market:

• Strategic corporate investors like Intel are backing AI chip startups like SambaNova, combining capital with manufacturing and distribution support to compete with NVIDIA's ecosystem.
• Late-stage venture firms are writing large checks into companies like Positron that have reached unicorn valuations, signaling confidence that inference hardware can become a significant standalone business.

The investor mix in Q1 2026 shows that both strategic and financial backers see room for new winners in the AI chip market, especially around inference.

Any big acquisitions or IPOs in the last three months in the AI chip market?

There hasn't been any big acquisitions or IPOs during Q1 2026 in the AI chip market, though the large funding rounds and strategic partnerships suggest that consolidation could pick up later in the year.

How are companies in the AI chip market performing overall?

We are watching this market everyday, because we need to constantly update our pitch deck. Here is a couple of things we have noticed.

Are there any standout success metrics or financial results in the AI chip market?

Q1 2026 was packed with record-breaking financial results across the AI chip market:

• NVIDIA posted quarterly revenue of $68.1 billion, with $62.3 billion coming from data centers, confirming that demand for AI accelerators is still growing at enormous scale.
• Broadcom reported Q1 AI revenue of $8.4 billion, up 106% year over year, proving that custom AI accelerators have become a multi-billion-dollar business.
• AMD reported record Q4 revenue of $10.3 billion and full-year revenue of $34.6 billion, entering 2026 with real scale in the AI chip market.
• Marvell reported record quarterly and full-year revenue, with all-time-high design wins driven by AI chip demand.
• FuriosaAI's RNGD chip entered mass production with 4,000 units delivered, a milestone most AI chip startups never reach.

The breadth of these results shows that AI chip market growth is not just an NVIDIA story anymore. Revenue gains are spreading to custom silicon makers, networking companies, and even smaller startups.

Have there been any major partnerships in the AI chip market?

Several major partnerships reshaped the competitive landscape of the AI chip market during Q1 2026:

• AMD and Meta announced an expanded strategic partnership to deploy 6 gigawatts of AMD GPUs, the largest publicly known AI chip deal and a major win for AMD in the data center.
• AMD and Nutanix formed a strategic partnership with a $250 million commitment to build an open AI platform for enterprise customers.
• IBM and NVIDIA expanded their collaboration to help enterprises move AI projects from pilots into production across data analytics, document processing, and regulated deployments.
• AMD and TCS partnered to bring Helios rack-scale AI architecture to India with a 200MW sovereign AI deployment plan.

The common thread in Q1 2026 partnerships is that AI chip companies are no longer just selling chips. They are building full-stack relationships that lock in demand for years.

Have there been any notable technology or infrastructure breakthroughs in the AI chip market?

Q1 2026 brought several meaningful technology milestones in the AI chip market:

• NVIDIA launched its Rubin platform, the next generation after Blackwell, claiming much lower inference token costs and fewer GPUs needed for large-model training.
• NVIDIA described the Vera Rubin platform as a complete AI factory blueprint with seven chips in full production, shifting the AI chip market conversation from individual chips to full-stack infrastructure.
• Microsoft unveiled Maia 200, a 3nm inference accelerator with 216GB of HBM3e and 7 TB/s memory bandwidth, designed to improve the economics of token generation at scale.
• Oracle operationalized rack-scale Blackwell deployments with dedicated APIs that let customers manage hundreds of NVIDIA GB200 NVL72 racks as individual AI supercomputers.

The big shift in Q1 2026 is that the AI chip market is moving from selling individual chips to designing entire AI factories, and that changes where value and opportunity sit in the market.

Have any companies restructured or shifted pricing or business model in the AI chip market?

We did not observe any major restructurings, pricing changes, or business model shifts during Q1 2026 in the AI chip market.

Are there any other notable wins or successes in the AI chip market?

A couple of other wins stood out during Q1 2026 in the AI chip market:

• SambaNova launched its SN50 chip, partnered with Intel, and raised over $350 million all at once, a rare triple announcement for a private AI chip company.
• Positron reached unicorn status with a $230 million Series B, showing that inference-first AI hardware startups can still attract large-scale investment.

Both SambaNova and Positron prove that in the AI chip market, there is still room for well-funded challengers, especially those focused on inference efficiency.

What is the overall sentiment in the AI chip market right now?

Are there any notable recent opinion pieces, thought leadership about the AI chip market?

One notable forecast stood out during Q1 2026:

• TrendForce projected that AI chip demand will push foundry revenue up 24.8% in 2026, noting that many cloud players and AI startups are pushing their own chip designs into volume production this year.

TrendForce's forecast reinforces the idea that AI chip demand is now reshaping not just the chip market itself but also the upstream manufacturing economics that support it.

Are there any interesting and recent market research reports about the AI chip market?

One research report stood out during Q1 2026:

• Dell'Oro Group published a report saying Blackwell, Rubin, and custom chips will be the main growth drivers for data center AI infrastructure in 2026, confirming that the AI chip market is widening rather than narrowing.

Dell'Oro's view supports what the financial results already showed: the AI chip market is broadening beyond a single vendor, and both merchant and custom silicon are growing at the same time.

Have there been any regulatory changes, policy updates, or new compliance requirements in the AI chip market?

One significant regulatory change happened during Q1 2026:

• The U.S. Bureau of Industry and Security revised its license review policy for advanced AI chips exported to China, moving to case-by-case review for products like the NVIDIA H200 and AMD MI325X if certain security conditions are met.

This policy shift could reopen a meaningful revenue stream for AI chip companies, but it also adds uncertainty since each export now depends on individual review rather than a blanket rule.

Who is the author of this content?

NEW MARKET PITCH TEAM

We track new markets so founders and investors can move faster

We build living “market pitch” documents for emerging markets: from AI to synthetic biology and new proteins. Instead of digging through outdated PDFs, random blog posts, and hallucinated LLM answers, our clients get a clean, visual, always-updated view of what’s really happening. We map the key players, deals, regulations, metrics and signals that matter so you can decide faster whether a market is worth your time. Want to know more? Check out our about page.

How we created this content 🔎📝

At New Market Pitch, we kept seeing the same problem: when you look at a new market, the data is either missing, paywalled, or buried in 300-page reports that feel like they were written in the 80s. On the other side, LLMs and random blog posts give you confident answers with no sources, and sometimes they just make things up. That’s not good enough when you’re about to invest real money or launch a company.

So we decided to fix the experience. For each market we cover, we build a structured database and update it on a regular basis. We track funding rounds, fund memos, M&A moves, partnerships, new products, policy changes, and the real activity of startups and incumbents. Then we turn all of that into a clear “market pitch” that shows where the opportunities are and how people actually win in that space.

Every key data point is checked, sourced, and put back into context by our team. That’s how we can give you both speed and reliability: fast coverage of new markets, without the usual guesswork.