Subquadratic - 2026 Pricing, Features, Reviews & Alternatives

Subquadratic is a cloud-based large language model inference API built on a fully subquadratic architecture, where computational cost scales sub-linearly with context length rather than growing quadratically as in standard transformer-based systems. This architectural distinction allows the platform to process extremely long contexts, up to 12 million tokens in a single prompt, at significantly lower latency and cost compared to conventional attention-based models. The API is designed for enterprise and developer teams that need to run inference over large volumes of text, including entire codebases, legal document collections, vendor contracts, or multi-session conversation histories, without the performance degradation typically associated with long-context workloads.

The platform exposes a REST API compatible with standard LLM tooling, allowing integration into existing pipelines with minimal friction. Subquadratic supports use cases across industries including software development, legal, finance, and research, where long-document comprehension and retrieval are critical. Teams can submit arbitrarily long inputs and receive coherent, context-aware outputs without chunking or summarization preprocessing. The cloud-based deployment model eliminates infrastructure management overhead, and usage-based pricing allows organizations to scale inference workloads according to demand without fixed capacity commitments.