
Fractile is building chips to run large language models two orders of magnitude faster. Existing hardware is good for training LLMs, but very poorly suited to subsequent inference of the trained model, which is increasingly the dominant workload. A network’s weights need to be moved onto a chip once per word generated, and this movement takes a few hundred times longer than the subsequent computations themselves. Fractile’s revolutionary approach to fusing computation with memory eliminates this bottleneck, and can scale to allow running the world’s largest models at a global scale.

Fractile is building chips to run large language models two orders of magnitude faster. Existing hardware is good for training LLMs, but very poorly suited to subsequent inference of the trained model, which is increasingly the dominant workload. A network’s weights need to be moved onto a chip once per word generated, and this movement takes a few hundred times longer than the subsequent computations themselves. Fractile’s revolutionary approach to fusing computation with memory eliminates this bottleneck, and can scale to allow running the world’s largest models at a global scale.
Product: Processors that physically interleave memory and compute to accelerate LLM inference
Headquarters: London, United Kingdom (team presence in London and Bristol)
Founded: 2022
Founder & CEO: Walter Goodwin
Funding: $17.5M total; currently Seed-stage
Employees: 71
| Company |
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Large language model (LLM) inference / AI hardware
2022
Computer Hardware Manufacturing
$15M
Company emerged from stealth with a $15M seed round; investor participation reported from Kindred Capital, NATO Innovation Fund, Cocoa, and Inovia Capital.
“Backed by technology- and science-focused investors including Oxford Science Enterprises and Kindred Capital, with participation from the NATO Innovation Fund and later involvement from Patrick Gelsinger and ARIA.”
Fractile is building silicon, systems and software which will redefine the frontier of AI: running the world’s most advanced models at radically higher speed and lower cost. We have an exceptional team across hardware and software capable of bringing about this change, and we are growing fast to meet demand and deliver our product at scale.
We’re looking for an engineer to develop and maintain system-level hardware defect detection tests for an AI accelerator server platform. The role is focused on implementing, executing, and improving tests used in factory assembly and service/repair environments to identify hardware defects quickly and reliably. Work closely with the System Test Engineering Lead to translate defect detection strategy into robust, repeatable test implementations rather than design validation.
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Export control and security clearance Certain roles may involve working on technologies subject to export restrictions. Applicants may be required to undergo additional eligibility checks to ensure compliance with applicable law.