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Description
Reforge artifacts provide a gateway to the experiences of previous experts in the field. By delving into the insights and narratives associated with each artifact, including notes from their creators, users can gain valuable perspectives. You can save artifacts for future reference or use them as prompts to facilitate knowledge sharing within your team. Equip your team with immediate access to comprehensive courses, templates, and case studies designed by leading tech professionals. Additionally, you can create customized learning journeys for your team's objectives through Collections, which are perfect for onboarding new hires, training emerging managers, and more. To further foster collaboration, the platform includes features like customizable templates, highlighting and tagging capabilities, and detailed guides that specifically target various challenges faced by teams. This ensures that all team members can work together effectively while pursuing their individual and collective goals.
Description
SubQ 1.1 Small is the second iteration of Subquadratic’s long-context AI model, built to help enterprises solve problems that require reasoning across entire artifacts rather than isolated chunks. The model is designed for use cases involving large code repositories, document libraries, legal agreements, financial reports, contracts, and other complex information sets. Its Subquadratic Sparse Attention architecture reduces the compute burden of traditional dense attention, making it more practical to process multi-million-token contexts. SubQ 1.1 Small achieves near-perfect performance on needle-in-a-haystack retrieval tests up to 12M tokens, despite being trained primarily at 1M tokens. It also performs strongly on RULER, GPQA Diamond, LiveCodeBench, and AutomationBench Finance, showing a balance between long-context retrieval and general reasoning ability. At 1M tokens, the model uses 64.5x less compute than dense attention and runs 56x faster than FlashAttention-2 on a single attention layer. This efficiency makes long-context training and inference more scalable for enterprise AI applications. SubQ 1.1 Small is especially valuable for teams that need to analyze relationships across full documents, trace logic across codebases, or connect information across extensive collections. The model is intended to help organizations reduce dependence on complex retrieval workarounds and reason more directly over large-scale data.
API Access
Has API
API Access
Has API
Integrations
Claude Code
OpenAI
OpenAI Codex
SubQ
Pricing Details
$1,995 per year
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Reforge
Website
www.reforge.com
Vendor Details
Company Name
Subquadratic
Founded
2026
Country
United States
Website
subq.ai/subq-1-1-small-technical-report
Product Features
Product Roadmap
Collaboration
Content Import / Export
Diagramming
Drag & Drop
Feature Management
Milestone Tracking
Prioritization
Requirements Management
Workflow Management