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Listicler
CoCalc

CoCalc

Collaborative calculation and data science in the cloud

Founded
2013
Starting Price
$0
Category
Education & Learning
Company Size
1-50 employees
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

  • Requires programming knowledge, steep for non-technical beginners
  • Free tier has restricted quotas and no internet access from projects
  • Pricing is fragmented across subscriptions, pay-as-you-go and licenses
  • Browser-based performance can lag dedicated local environments for heavy tasks

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.

Collaborative Whiteboard

A computational whiteboard mixes free-form sketching with live code cells for brainstorming and teaching.

LaTeX Editing

Full LaTeX environment with live preview, forward/inverse search and synchronized collaborative editing.

Pay-As-You-Go Billing

Compute servers and upgrades can be billed by usage, charging only while resources are actually running.

Pricing

Free
$0/month
  • Trial projects with limited quotas
  • Jupyter, SageMath, LaTeX and terminals
  • Real-time collaboration
  • No internet access from projects
Subscriptions
Custom
  • Upgrade memory, CPU and disk per project
  • Member-only hosting for better reliability
  • Internet access from projects
  • Applied to your projects or any you collaborate on
Pay-As-You-Go
Usage-based
  • On-demand compute servers
  • Optional GPUs from T4 to H100
  • Charged only while running
  • Scale resources up and down freely
Courses
Custom
  • Discounted academic licenses
  • Per-student upgrade distribution
  • nbgrader auto-grading
  • Self-service or purchase order

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.

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