Subquadratic vs FinishUP

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Subquadratic compared with FinishUP
Detail	Subquadratic	FinishUP
What it does	Efficiency is Intelligence	Agents start, FinishUP checks
Stage	Startup	Not given
Founded	Not given	Not given
Based in	US	Not given
Pricing model	Paid	Open source
Pricing	Free 100M tokens for new users. $0.04 per 1M tokens for input tokens.	Free
Key features	384K token context window Multimodal input support 100K tokens processed in less than a second Structured output for direct code use Subquadratic Sparse Attention algorithm for efficient compute $0.04 per 1M tokens pricing Customer content not used for model training Data retention limited to 60 days	Records and checks work evidence Identifies remaining open tasks Local checks on your computer Optional AI-powered review Compatible with Codex, Claude Code, and Cursor
What makes it different	First long-context decision model purpose-built for enterprise work Frontier-level decision-making performance at 5-10x lower cost than frontier LLMs Tied for #1 on Artificial Analysis Decision Index Processes entire codebase or data room in single context window Speeds agent reasoning from minutes to seconds	Open source with no licensing costs Local verification without sending data to external services Prevents AI agents from drifting or forgetting task progress
Community votes	0	0
DR (Domain Rating by Ahrefs)	52 +1 (up) since last check	Not checked yet no change since last check
Trust Flow (Majestic)	17	0
Citation Flow (Majestic)	37	0
Referring domains (Majestic)	654	0

5 details filled in for both companies.