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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

LM Studio Bionic serves as an AI assistant designed to facilitate productive work utilizing open models in areas such as coding, research, document management, and general knowledge tasks. Users have the option to run models flexibly either on their local devices, via LM Link, or through advanced open-source models in the LM Studio Secure Cloud for more resource-intensive operations. The local models rely on the LM Studio runtime, which can be conveniently downloaded directly within the application, while cloud-based requests adhere to a Zero Data Retention policy, ensuring that no data is stored post-processing. For coding purposes, users can link a local folder as a Code project, enabling Bionic to analyze the codebase, clarify complex logic, search for pertinent files, track code behavior, make edits, or troubleshoot problems. The inclusion of inline diffs simplifies the review process as changes are implemented. Furthermore, work projects encompass a variety of formats such as documents, PDFs, presentations, and spreadsheets, empowering Bionic to create new files, organize existing materials, summarize key content, and enhance current projects, thereby streamlining the workflow and boosting overall efficiency. With these capabilities, LM Studio Bionic stands out as a comprehensive tool for modern-day productivity.

Description

tensorViz provides a platform for developers to delve into PyTorch models and JAX/Flax programs through dynamic graph visualizations. In the case of PyTorch, users have the ability to open nested modules, examine tensor shapes recorded during a single forward pass, navigate to the corresponding Python source code, and observe architectural modifications alongside code differences. The site additionally features pre-recorded model graphs for users to analyze without the need for any installation. A free extension for VS Code can be found in both the Visual Studio Marketplace and Open VSX. For local capture, users must have Python installed along with the necessary model dependencies and sample inputs. There are also standalone coding-agent plugins that are currently in preview for Apple Silicon macOS; MCP agents can establish connections with the extension as well. While JAX/Flax graphs utilize CPU tracing to infer shapes, it is important to note that source edits for PyTorch models are not applicable in this context. By offering a seamless experience for both frameworks, tensorViz enhances the development and debugging process for users.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

No images available

Integrations

Claude Code No 
Codex CLI No 
Cursor No 
GLM-5.2 Yes 
GLM-5.3 Yes 
GitHub No 
JavaScript Yes 
Kimi K2.7 Code Yes 
LM Studio Yes 
Mistral AI Yes 
Model Context Protocol (MCP) No 
Python Yes 
T3 Code No 
Visual Studio Code No 
Voxtral Yes 

Integrations

Claude Code Yes 
Codex CLI Yes 
Cursor Yes 
GLM-5.2 No 
GLM-5.3 No 
GitHub Yes 
JavaScript No 
Kimi K2.7 Code No 
LM Studio No 
Mistral AI No 
Model Context Protocol (MCP) Yes 
Python No 
T3 Code Yes 
Visual Studio Code Yes 
Voxtral No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

$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 Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
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 No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

LM Studio

Founded

2023

Country

United States

Website

lmstudio.ai/blog/introducing-lm-studio-bionic

Vendor Details

Company Name

tensorViz

Website

tensorviz.dev/

Product Features

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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