Sold by: TuringQ Co. Ltd.
Deployed on AWS
AWS Free Tier
Quantum-Inspired Hybrid Solver (QIH Solver) is good at quickly giving high-quality solutions to large-scale combinatorial optimization problems in the form of the Ising model or QUBO.
Overview
TuringQ Quantum-Inspired Hybrid Solver (QIH Solver) consists of a quantum-inspired optimization algorithm hybridized with several classical heuristics for complex combinatorial optimization problems. Through ingenious design, the TuringQ QIH Solver can automatically select appropriate algorithm parameters according to the characteristics of the problem and give a good enough solution in a short time.
In the era of noisy intermediate-scale quantum (NISQ), TuringQ QIH Solver provides an alternative for users willing to experience the advantages of quantum computing technology. With the maturity of hardware manufacturing technology, we are considering implementing core algorithms on quantum hardware. In this context, TuringQ QIH Solver may serve as a smooth transition to the era of quantum computing and help users gain more benefits from quantum computing technology.
TuringQ QIH Solver can be applied in transportation and logistics, job scheduling, financial technology, de novo drug design, and other fields where huge optimization problems demand fast solutions.
Highlights
- Fast calculation speed and high-quality solution. Compared with similar products, it can give better solutions.
- Easy to use and low equipment requirements. QIH Solver can analyze features and adjust parameters automatically. Only the python environment and CPU are needed.
- The larger the dimension, the greater the advantages. For a 15000-dimensional QUBO problem, traditional heuristics takes 2 hours, while TuringQ QIH Solver can get a better solution within 2 minutes.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimensions summary
You run this quantum-inspired hybrid solver at no software charge across many EC2 instance types, all billed hourly. The dimensions are not tiers or feature levels. Each one maps to a specific compute instance, so your choice sets the underlying capacity you rent. Options span burstable T2 and T3 families for lighter, variable workloads and compute-optimized C3, C4, and C5 families for heavier processing. Larger sizes within each family provide more CPU and memory. The solver needs only a Python environment and CPU, so pick the instance that fits your problem size and memory needs.
Top-of-mind questions for buyers
Each dimension bills per hour of a specific EC2 instance type. One unit is one running instance-hour of that named instance. Your choice sets the CPU and memory you rent. Larger sizes within a family carry more capacity. The solver software itself carries no charge.
The software charge is free, so no software fees accrue regardless of state. Hourly metering applies only while an instance runs. Stopped instances stop accruing hourly compute charges, though AWS may still bill underlying storage attached to them. Restarting resumes hourly metering.
You need only a Python environment and a CPU. The solver analyzes your problem and sets algorithm parameters automatically, so no manual tuning is required. There is no cap on compute nodes; scale depends on the memory available on the instance you choose.
www.turingq.com
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
v1.1.2 Initial Iteration Release
Additional details
Usage instructions
TuringQ Quantum Marketplace Solver Guide
Access the full solver experience: https://www.turingq.com/qihsolver
Activation command: turingq-qih-activate <activation_code>
Steps to Use:
-
Launch an EC2 Instance
- Recommended instance type: c5.4xlarge
- Use the provided AMI image
- Wait a few minutes after startup for the instance to be ready
-
Login to Your Instance
- ssh ubuntu@<instance_ip>
-
Navigate to the Main Directory
- cd qheuristic/
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Upload Your Matrix File
- Place your matrix file in the qheuristic/ directory
-
Edit Your Python Script
- Refer to the provided example test.py
- Modify it to suit your own task
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Run the Python Script
- python XX.py
-
Check the Results
- The output will be saved as a .txt file in the same directory
-
(Optional) Test the Environment
- Run the example test.py to verify your instance configuration
Resources
Vendor resources
Support
Vendor support
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