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Subquadratic
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Research-stage sub-quadratic LLM built for multi-million-token reasoning across full codebases and long agent histories.

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Pricing

No public pricing

Core features
  • Up to 12M-token context window
  • Sub-quadratic sparse-attention architecture (claimed ~1000x less attention compute at scale)
  • OpenAI-compatible API with streaming and tool use
  • Coding-agent plugin that offloads token-heavy context work
  • Benchmarked long-context retrieval and reasoning performance
Use cases
  • Reasoning across an entire code repository in one call
  • Maintaining long-running agent state without quality loss
  • Reducing compute cost for long-context AI applications
  • Speeding up coding agents on large codebases
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