Infinity
Category: AI Infrastructure
AI infrastructure company building a universal inference software layer that enables any AI chip to run inference workloads, challenging Nvidia's CUDA dominance. Infinity was founded in 2025. The company is led by Jeremy Nixon. Based in San Francisco, California, United States. Team size: 11-50. Total funding raised: $15M. Latest round: Seed. Key investors include Touring Capital, Principal VC, Researchers from OpenAI, Researchers from Anthropic, Executives at major chip companies, Prominent angel investors.
- Founded
- 2025
- Headquarters
- San Francisco, California, United States
- Team size
- 11-50
- Total funding
- $15M
Value proposition
Infinity's autonomous AI agent Ignition automatically generates, tests, and optimizes low-level compute kernels for any AI chip architecture, reducing what takes months or years to hours or days, enabling non-Nvidia chips to achieve CUDA-level inference performance.
Products and solutions
Ignition — an AI research agent that autonomously generates, tests, debugs, and optimizes low-level compute kernels for AI inference on any chip architecture. Features: autonomous kernel generation, recursive self-improvement (RSI) feedback loop, cross-architecture generalization, human-in-the-loop steering.
Unique value
First AI-native approach to kernel generation that automates the entire inference software stack for any chip — reducing development timelines from years to days. No upfront license fee; revenue model based on performance gains (tokens/second improvements).
Target customer
AI chip manufacturers (semiconductor companies), cloud providers, and hardware companies building non-Nvidia AI accelerators (SRAM, GPUs, phone chips, Systolic Arrays)
Industries served
AI Infrastructure, Semiconductor / Chip Design, Cloud Computing, AI Inference Hardware
Technology advantage
Proprietary AI research agent (Ignition) with Recursive Self-Improvement (RSI) that continuously learns from real-world performance data. Demonstrated ability to reach 92% of theoretical peak performance on new chip architectures within 10 hours, and run frontier models (Qwen3, Qwen3.5, Gemma4) end-to-end within 10 days on previously unsupported hardware.
How they differentiate
Unlike Modular which provides a new programming language (Mojo) and compiler, Infinity uses an autonomous AI agent (Ignition) to auto-generate kernels without requiring developers to learn new languages. Unlike NVIDIA's proprietary CUDA ecosystem, Infinity is hardware-agnostic and works across any chip architecture. Unlike traditional manual kernel optimization, Infinity's agent automates the entire process with recursive self-improvement.
Main competitors
Modular (Mojo/MAX platform), NVIDIA (CUDA/TensorRT-LLM), AMD (ROCm)
Key partnerships
d-Matrix (AI chip maker, live design partnership powering the Infinity d-Matrix Cloud), in active discussions with other major chip companies and cloud providers
Notable customers
d-Matrix (AI chip company)
Major milestones
Founded August 2025 by Jeremy Nixon, Raised $15M seed at $100M valuation (July 2026), Launched Ignition AI agent, Achieved 92% theoretical peak performance on d-Matrix Corsair chip within 10 hours, Ran Qwen3, Qwen3.5, and Gemma4 end-to-end on d-Matrix hardware within 10 days, Improved Qwen3-8B inference throughput by 34% over vLLM in one day
Growth metrics
Generating millions of dollars in ARR from chip design partnerships (as of July 2026); 26 employees; $100M post-money valuation
Market positioning
Early-stage disruptor in the AI inference software layer, positioned as a CUDA alternative for non-Nvidia chips. Part of a wave of startups chipping away at Nvidia's ~80% data-center AI accelerator market share by solving the software bottleneck for alternative hardware.
Geographic focus
Global (headquartered in San Francisco, US)
About Jeremy Nixon
Ex-Google Brain Researcher; Math @ Harvard University. Co-founder of AGI House (global AI hacker network). Creator of the Omega machine learning algorithm.
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Official website: https://infinity.inc