Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Cohere’s Command A Reasoning stands as the company’s most sophisticated language model, specifically designed for complex reasoning tasks and effortless incorporation into AI agent workflows. This model exhibits outstanding reasoning capabilities while ensuring efficiency and controllability, enabling it to scale effectively across multiple GPU configurations and accommodating context windows of up to 256,000 tokens, which is particularly advantageous for managing extensive documents and intricate agentic tasks. Businesses can adjust the precision and speed of outputs by utilizing a token budget, which empowers a single model to adeptly address both precise and high-volume application needs. It serves as the backbone for Cohere’s North platform, achieving top-tier benchmark performance and showcasing its strengths in multilingual applications across 23 distinct languages. With an emphasis on safety in enterprise settings, the model strikes a balance between utility and strong protections against harmful outputs. Additionally, a streamlined deployment option allows the model to operate securely on a single H100 or A100 GPU, making private and scalable implementations more accessible. Ultimately, this combination of features positions Command A Reasoning as a powerful solution for organizations aiming to enhance their AI-driven capabilities.
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
No
API Access
Has API
Yes
Integrations
Claude Code
No
Cohere
Yes
Hugging Face
Yes
OpenAI
No
OpenAI Codex
No
SubQ
No
Integrations
Claude Code
Yes
Cohere
No
Hugging Face
No
OpenAI
Yes
OpenAI Codex
Yes
SubQ
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Cohere AI
Founded
2019
Country
Canada
Website
cohere.com/blog/command-a-reasoning
Vendor Details
Company Name
Subquadratic
Founded
2026
Country
United States
Website
subq.ai/subq-1-1-small-technical-report