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What is tensorViz?

tensorViz offers a unique platform that allows developers to explore PyTorch models and JAX/Flax programs through interactive graph visualizations. For PyTorch, users can delve into nested modules, inspect tensor shapes captured during a single forward pass, navigate to the related Python source code, and witness architectural changes along with code variations. The platform also includes pre-recorded model graphs that can be analyzed without any installation requirements. A free extension compatible with VS Code is available on both the Visual Studio Marketplace and Open VSX. To enable local capture, users need to have Python installed along with the relevant model dependencies and sample inputs. Additionally, there are standalone coding-agent plugins in preview specifically designed for Apple Silicon macOS, allowing MCP agents to connect seamlessly with the extension. While JAX/Flax graphs rely on CPU tracing to determine shapes, it's crucial to understand that source modifications for PyTorch models do not apply in this scenario. By providing a cohesive experience for both frameworks, tensorViz significantly improves the development and debugging workflow for its users, ultimately leading to more efficient coding practices. This dual framework support ensures that developers have the tools they need to effectively manage their projects and enhance their productivity.

What is RunMat?

RunMat eliminates MATLAB license costs while delivering faster performance. Teams can run existing .m scripts and workflows without rewriting code or purchasing per-seat licenses. GPU acceleration is automatic -- no code changes required. Engineers get results up to 131x faster than NumPy on dense numerical workloads, accelerating parameter sweeps, simulations, and data processing pipelines. Deploys anywhere: desktop (Windows, macOS, Linux), browser (no install needed), CI/CD pipelines, and Jupyter notebooks. Single portable binary with no dependencies. MIT licensed with no seat limits. Ideal for engineering teams in signal processing, controls, quantitative finance, imaging, and scientific computing who need high-performance numerical tools without proprietary license overhead.

Media

No images available

Media

Integrations Supported

GitHub
Claude Code
Codex CLI
Cursor
Model Context Protocol (MCP)
T3 Code
Visual Studio Code

Integrations Supported

GitHub
Jupyter Notebook
MATLAB
npm

API Availability

Has API

API Availability

Pricing Information

$0
The VS Code extension is free to install. Core graph exploration and source-edit forms work without an agent or provider API key; connecting a coding agent is optional.
Free Version

Pricing Information

$0
Free, Open Source. MIT licensed runtime with no seat limits. Cloud plans available for collaboration and team features.
Free Version

Supported Platforms

SaaS
Windows
Mac
Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

tensorViz

Company Website

tensorviz.dev/

Company Facts

Organization Name

RunMat

Date Founded

2022

Company Location

United States

Company Website

runmat.com

Categories and Features

Deep Learning

Not specified

Machine Learning

Not specified

Categories and Features

Computer-Aided Engineering (CAE)

Fluid Dynamics
Import / Export Files
Manufacturing Process Simulation
Mechanical Event Simulation
Thermal Analysis

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