AI Chips & Hardware
Last updated: April 2026
Custom silicon for AI workloads — from NVIDIA GPUs to custom ASICs by Cerebras, Groq, and others. This is the infrastructure layer everything else runs on.
Why It Matters in 2026
The AI hardware market is experiencing unprecedented demand and innovation. NVIDIA's dominance is being challenged by custom silicon from Cerebras, Groq, AMD, and cloud providers building their own chips.
In 2026, the bottleneck for AI progress is compute, not algorithms. Companies that can deliver faster, cheaper inference and training at scale hold enormous strategic value.
New architectures — from wafer-scale chips to photonic computing — are pushing the boundaries of what's physically possible. The hardware layer is where the next order-of-magnitude improvements in AI performance will come from.
Key Companies
10 trackedCoreWeave
AI Infrastructure
$49.0B
score
Graphcore
AI Infrastructure
$500M
score
Scale AI
AI Infrastructure
$29.0B
score
Nebius
AI Infrastructure
$25.0B
score
Nscale
AI Infrastructure
$14.6B
score
Fireworks AI
AI Infrastructure
$4.0B
score
Lambda Labs
AI Infrastructure
$4.0B
score
Tenstorrent
AI Infrastructure
$3.2B
score
Groq
AI Infrastructure
$20.0B
score
Baseten
AI Infrastructure
$5.0B
score
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Explore trend →Frequently Asked Questions
Why is AI hardware important?
AI workloads require massive parallel computation. Specialized hardware (GPUs, TPUs, custom ASICs) determines the speed, cost, and energy efficiency of training and deploying AI models.
Does NVIDIA dominate AI chips?
NVIDIA holds approximately 80% of the AI training chip market with its H100 and B200 GPUs. However, AMD, Intel, and startups like Cerebras and Groq are competing aggressively.
What are AI inference chips?
Inference chips are optimized for running trained models rather than training them. Companies like Groq, SambaNova, and cloud providers are building specialized inference hardware for faster, cheaper AI deployment.
How much does AI compute cost?
Training a frontier model can cost $100M+. Inference costs vary widely but are dropping rapidly. Cloud GPU instances range from $1-$30/hour depending on the chip and provider.