AI Chat - qBraid

qBraid AI Chat is the most capable AI assistant for quantum computing on the qBraid platform. Whether you’re exploring quantum devices, tracking your jobs, or planning your learning journey, the AI Chat provides intelligent, context-aware responses powered by our in-house MCP server.

How It Works

The AI Chat is powered by qBraid’s Model Context Protocol (MCP) server, which provides the underlying language model with crucial real-time context about:

Live quantum device statuses and specifications
Your quantum job history and results
qBraid platform capabilities and documentation
Quantum computing concepts and best practices

This means you get accurate, up-to-date answers rather than responses based on potentially outdated training data.

Accessing AI Chat

Open your qBraid Lab instance
Click the AI Chat icon in the left sidebar
Type your question and press Enter

Example Use Cases

Explore what you can accomplish with AI Chat through these example prompts:

Quantum Devices
Quantum Jobs
Learning Pathway

Exploring Quantum Devices

Ask the AI about available quantum devices, their specifications, and current status.Example prompt:

What quantum devices are currently available on qBraid?
I'm looking for a device with at least 20 qubits that supports
native two-qubit gates. Can you compare the options and their pricing?

The AI will provide:

List of matching devices with specifications
Current online/offline status
Queue depths and estimated wait times
Pricing in qBraid credits
Recommendations based on your requirements

Managing Quantum Jobs

Get insights into your quantum job history, check statuses, and retrieve results.Example prompt:

Show me my recent quantum jobs from the past week.
Which ones have completed successfully and what were their results?
Were there any failures I should investigate?

The AI will provide:

Summary of your recent jobs
Status breakdown (completed, failed, running, queued)
Results and measurement counts for completed jobs
Error analysis for failed jobs
Cost breakdown in credits

Personalized Learning

Get customized recommendations for learning quantum computing based on your background and goals.Example prompt:

I'm a software developer with Python experience but new to quantum computing.
I want to learn how to run variational algorithms on real hardware.
Can you create a learning pathway for me using qBraid resources?

The AI will provide:

Structured learning path tailored to your experience
Recommended qBraid tutorials and notebooks
Suggested environments to install
Hands-on exercises with increasing complexity
Resources for specific topics (VQE, QAOA, etc.)

Tips for Effective Prompts

Be Specific

Instead of “Tell me about devices,” try “What’s the qubit count and connectivity of the IonQ Aria device?”

Provide Context

Mention your experience level, the quantum framework you’re using (Qiskit, Cirq, etc.), and your end goal.

Ask Follow-ups

The AI maintains conversation context, so you can ask clarifying questions or dive deeper into any topic.

Request Code Examples

Ask for code snippets in your preferred framework — the AI can generate working examples for qBraid Lab.

What’s Next

Ready to go beyond chat? Learn how Agent Mode enables you to execute complete quantum workflows directly from natural language commands.

User Guide

​How It Works

​Accessing AI Chat

​Example Use Cases

​Exploring Quantum Devices

​Managing Quantum Jobs

​Personalized Learning

​Tips for Effective Prompts

​What’s Next

How It Works

Accessing AI Chat

Example Use Cases

Exploring Quantum Devices

Managing Quantum Jobs

Personalized Learning

Tips for Effective Prompts

What’s Next