d-Matrix vs NVIDIA
Side-by-side comparison of AI visibility scores, market position, and capabilities
d-Matrix builds in-memory AI inference accelerator chips (Corsair) that deliver 10x faster inference at 3x lower cost than GPU-based systems; raised $275M Series C at a $2B valuation in November 2025; Raptor chip due 2026.
About
d-Matrix is a Santa Clara-based AI semiconductor company founded in 2019, developing purpose-built inference accelerator hardware that challenges Nvidia''s dominance in AI compute. Its flagship Corsair inference accelerator card uses in-memory computing (IMC) architecture — performing computations directly inside the memory arrays rather than moving data between separate processing and memory units. This eliminates the "memory wall" bottleneck that limits GPU-based inference performance for large language models and generative AI workloads, enabling what d-Matrix claims is 10x faster inference, 3x lower cost, and 3–5x better energy efficiency versus GPU systems.
H200/GB200/Blackwell GPU family powering 90%+ of AI training workloads; $130B+ quarterly revenue run-rate; $3T+ market cap; 85% of revenue from AI compute. Every major AI company — OpenAI, Anthropic, Google, Meta, xAI — runs on NVIDIA hardware.
About
NVIDIA Corporation is a Santa Clara, California-based semiconductor and AI computing company — publicly traded on the NASDAQ (NASDAQ: NVDA) as an S&P 500 Information Technology component and member of the Dow Jones Industrial Average — designing and supplying graphics processing units (GPUs), AI accelerators, networking infrastructure, and computing platforms for data center AI training and inference, gaming, professional visualization, and automotive applications through approximately 36,000 employees worldwide. In fiscal year 2025 (ending January 2025), NVIDIA reported revenues of $130.5 billion (+114% year-over-year) — driven by unprecedented demand for H100 and H200 AI GPU clusters from hyperscale cloud providers (Microsoft Azure, Amazon Web Services, Google Cloud), AI-native companies (OpenAI, Anthropic, xAI, Cohere), and enterprise AI deployments — making NVIDIA the fastest-growing large-cap company in recorded history and the third-most-valuable company globally (market capitalization exceeding $3 trillion in 2024-2025). CEO Jensen Huang has led NVIDIA's transformation from a gaming GPU company into the foundational infrastructure provider for the artificial intelligence economy: NVIDIA's CUDA (Compute Unified Device Architecture) software platform — developed since 2006 — has accumulated 4+ million developers, 4,000+ GPU-accelerated applications, and a decade of AI research papers, libraries, and frameworks (PyTorch, TensorFlow, cuDNN) optimized for NVIDIA hardware, creating the most powerful software moat in technology. The Blackwell GPU architecture (B100, B200, GB200 — launched 2024, ramping production in 2025) delivers 5x training performance improvement over the H100, sustaining NVIDIA's generational performance advantage that justifies continued AI capital expenditure at $300-500 billion annual industry pace.
Key Details
Capabilities & Ecosystem
Capabilities
Integrations
Also Compare
Track AI Visibility in Real Time
Monitor how your brand performs across ChatGPT, Gemini, Perplexity, Claude, and Grok daily.