Base Compute

An AI inference lab building runtimes and infrastructure that enable powerful AI models to run on-device, solving latency, privacy, and cost issues associated with cloud-based inference. It sells to developers, IT teams, and enterprises seeking on-premise, hybrid, or air-gapped AI deployment. The approach is differentiated by hardware-specific optimization, achieving significant speedups over alternatives like llama.cpp and MLX, and by offering a zero marginal cost model once deployed on existing hardware.

Key features

• Prefill up to 6.4x faster than llama.cpp
• Decode up to 1.33x faster than MLX
• On-device inference for privacy
• Zero marginal cost per token
• On-premise, hybrid, or air-gapped deployment
• Automated research pipelines
• GPU kernels tuned per hardware and model