
Location
Headquarters: Mountain View, California, United States, North America
Region: California
Country: US
Continent: North America
About
MatX designs hardware tailored for the world’s best AI models, focusing on high-throughput chips and optimized interconnects to maximize performance for large models. They target cost-efficient training and production inference for extremely large transformer-based models, offering scale-out capabilities across hundreds of thousands of chips and low-level hardware control for expert users. Their technology aims to enable faster access to state-of-the-art models and higher performance-per-dollar in data center AI workloads, with emphasis on 7B-class to 20B+-parameter dense and mixture-of-experts models and scalability to 10T-class models. Based on information presented, their operations appear global with emphasis on AI model training and inference hardware.
MatX designs high-performance hardware tailored for large AI models, focusing on high-throughput chips and optimized interconnects. The company targets AI labs and data centers, offering scale-out capabilities for training and inference of transformer-based models. Their technology aims to provide cost-efficient computing power for extremely large models.
MatX Inc.
2022
for_profit
active
Industries
Primary Industry: Business Services
Categories
Funding & Financials
Series A
125000000
private
Investors
Founders
Mike Gunter
Reiner Pope
Leadership
Technology Stack
Products
SPIRe: A draft model designed to increase throughput in speculative decoding for large language models by combining sparse KV cache, pruned initialization, and feedback memory.
seqax: A minimalist, research-focused LLM codebase implemented in JAX, designed for small-to-medium scale pretraining research with explicit math, memory usage, and parallelism.
Sparse Multi Value Attention (SMVA): An attention mechanism that reduces KV cache memory bandwidth by using one key head and multiple sparsely accessed value heads to maintain model quality while lowering resource demands.
Funding rounds
Series B · $500M · (2026-02-24) · Lead: Jane Street Capital,Situational Awareness
Series A · $100M · (2024-11-22) · Lead: Spark Capital
Seed · $25M · (2024-03-26) · Lead: Nat Friedman