CoCalc
Collaborative calculation and data science in the cloud
Founded
2013
Starting Price
$0
Category
Education & Learning
Last updated June 4, 2026
About CoCalc
CoCalc is a cloud-based platform from SageMath, Inc. for real-time collaborative computation, supporting Jupyter Notebooks, SageMath, Python, R, Julia, Octave, LaTeX and Linux terminals directly in the browser. It bundles a pre-installed scientific software environment, optional GPU compute servers, integrated AI assistance, and full course-management tooling for teaching. Formerly known as SageMathCloud, it is widely used by researchers, educators and students who need a zero-setup environment for technical work.
Pros & Cons
Pros
- Zero local setup with thousands of pre-installed scientific packages
- Strong real-time collaboration on notebooks, LaTeX and worksheets
- Excellent for teaching with built-in course and auto-grading tools
- Pay-as-you-go GPU compute servers for ML workloads
- TimeTravel edit history and automatic backups protect your work
Cons
Key Features
Real-Time Collaboration
Multiple users edit Jupyter Notebooks, LaTeX documents, SageMath worksheets and whiteboards simultaneously with synced changes.
Cloud Jupyter Notebooks
Run Jupyter Notebooks in the browser with no local installation, across Python, R, Julia, SageMath, Octave and more.
GPU Compute Servers
Spin up dedicated compute servers with optional GPUs (T4 through H100) for heavier workloads and machine learning.
Integrated AI Assistance
Built-in generative AI models help generate code, explain output and fix errors inside notebooks and editors.
Pre-Installed Software Environment
Thousands of scientific and data-science packages come pre-installed, eliminating dependency and setup friction.
Course Management & Grading
Create courses, distribute assignments to students and auto-grade with nbgrader for classroom use.
TimeTravel History
Step through a complete edit history of any document to recover earlier states or audit changes.
Pricing
Free
$0/month
- Trial projects with limited quotas
- Jupyter, SageMath, LaTeX and terminals
- Real-time collaboration
- No internet access from projects
Subscriptions
Best For
Teaching Technical Courses
Instructors run entire math, data science or programming courses with shared projects, distributed assignments and automated grading.
Collaborative Research
Research teams co-edit notebooks and LaTeX papers in real time with a reproducible, shared computational environment.
Machine Learning Experiments
Data scientists launch on-demand GPU compute servers to train and test models without managing infrastructure.
Reproducible Data Science
Analysts work in a pre-configured environment with full edit history, ensuring results can be reproduced and audited.
