QuantumXLabs Reports Approximately 16.8x Acceleration Over CPU-Based Computing in Quantum-Enabled Analysis of More Than 7 Billion Gene Combinations Using Real-World Clinical Data
The GPU-accelerated analysis produced the same qualifying gene-triplet results as the CPU-only implementation.
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Rhea-AI Summary
Quantum X Labs (QXL) reported approximately 16.8-fold computational acceleration over CPU-only computing in a GPU-accelerated quantum-simulation benchmark using real clinical data. Its CliniQuantum subsidiary analyzed gene-expression data from 11 patients and 3,531 features, searching 7,331,162,245 possible three-gene combinations. A predefined minimum correlation threshold yielded approximately 22.2 million qualifying gene triplets.
The analysis took approximately 8.4 hours with 64 vCPUs versus approximately 0.5 hours with one NVIDIA T4 GPU on the same machine, producing the same qualifying results. The benchmark assessed computational performance, not clinical validity, predictive value or utility. The company intends to advance toward more complex configurations and larger biomedical datasets, while progressing from simulation and validation toward execution on quantum computing hardware.
Positive
- Minor pointApproximately 16.8-fold acceleration reduced analysis time from approximately 8.4 hours to approximately 0.5 hours, with identical qualifying results.
- Minor point7,331,162,245 possible three-gene combinations were searched, identifying approximately 22.2 million triplets meeting a predefined correlation threshold.
- Minor point. Forward-looking: it has not happened yet and may not happen.Development plans include more complex configurations, larger biomedical datasets and progression toward quantum computing hardware execution.
Negative
- Minor pointClinical validity, predictive value and potential utility of identified gene combinations were not evaluated or established.
- Minor point. Forward-looking: it has not happened yet and may not happen.Quantum simulation underlies the benchmark; execution on quantum computing hardware remains a development goal.
Key Figures
- Computational acceleration
- Approximately 16.8-fold
- GPU-accelerated quantum-simulation platform compared with CPU implementation
- Analysis time
- Approximately 8.4 hours vs approximately 0.5 hours
- 64 vCPUs vs one NVIDIA T4 GPU; same qualifying gene-triplet results
- Dataset size
- 11 patients; 3,531 gene-expression features
- Real clinical gene-expression dataset used in the evaluation
- Three-gene combinations searched
- 7,331,162,245 possible combinations
- Combinations generated from 3,531 genes
- Correlated gene triplets identified
- Approximately 22.2 million
- Identified using a predefined minimum correlation threshold
Previous Clinical trial Reports
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Reported an end-to-end quantum-enabled clinical-data workflow using real-world information on a simulator.
24h Move is the share-price change in the day after each event; other market factors may also have contributed.
Key Terms
gene-expression medical
vcpu technical
biomarker discovery medical
patient stratification medical
AI-generated analysis. How Rhea-AI works. Not financial advice.
The demonstration represents another development milestone in the Company’s development of quantum-enabled platform for high-dimensional clinical data analysis
Tel Aviv, Israel, Oct. 06, 2026 (GLOBE NEWSWIRE) -- Quantum X Labs Inc. (Nasdaq: QXL) (“Quantum X” or the “Company”), an advanced technologies company, today reported its GPU-accelerated quantum-simulation platform achieved an approximately 16.8-fold computational acceleration using a single machine with 64 cores (x86_64) and a single NVIDIA T4 Tensor Core GPU compared with the same 64-vCPU machine with only CPU implementation.
The evaluation used a real clinical gene-expression dataset comprising 11 patients and 3,531 gene-expression features, representing a challenging high-dimensional setting in which the number of biological variables greatly exceeds the number of patients.
Quantum X’s proprietary algorithm, operated through its subsidiary CliniQuantum, searched for correlated three-gene configurations across the dataset. The 3,531 genes generated 7,331,162,245 possible three-gene combinations. Using a predefined minimum correlation threshold, the algorithm identified approximately 22.2 million correlated gene triplets.
The analysis required approximately 8.4 hours using 64 vCPUs, compared with approximately 0.5 hours when accelerated using a single NVIDIA T4 GPU, while producing the same qualifying gene-triplet results.
“This represents an important development milestone for Quantum X Labs,” said Dr. Tidhar Turgeman, head of clinical trials data analysis. “Clinical and molecular datasets can contain thousands of variables but relatively few patients, creating enormous combinatorial search spaces. Demonstrating the ability to evaluate more than 7.3 billion potential gene combinations on real clinical data marks an important step in our development. The significant GPU acceleration further supports our continuing development of scalable, quantum-enabled approaches for biomarker discovery and patient stratification.”
The benchmark was conducted on an AWS g4dn.16xlarge EC2 machine using IBM Qiskit Aer GPU-based quantum simulation, with an NVIDIA T4 Tensor Core GPU. The benchmark was designed to evaluate computational performance and did not evaluate or establish the clinical validity, predictive value, or potential utility of any identified gene combinations.
QuantumXLabs intends to continue advancing its algorithms toward the analysis of increasingly complex multi-feature configurations and larger biomedical datasets, while progressing its development pathway from simulation and validation toward execution on quantum computing hardware.
Quantum X Labs Inc.
Quantum X Labs Inc. and its subsidiaries are focused on quantum technology, digital advertising and computing and enterprise artificial intelligence (AI) solutions. Quantum X Labs Ltd. is focused on developing and promoting quantum algorithms for the transportation, drug discovery and security segments as well as developing quantum- based GPS replacement and quantum atom accuracy solutions. Gix Media develops a variety of technological software solutions, which perform automation, optimization and monetization of internet campaigns, for the purposes of acquiring and routing internet user traffic to its customers. Metagramm is a developer of grammatical error correction software and offers tools for writing and reviewing, grammar, spelling, punctuation and style features, as well as translation and multilingual dictionaries, using artificial intelligence and machine learning technology.
For more information about Quantum X Labs, visit https://quantumxlabs.xyz/
Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the “safe harbor” provisions of the Private Securities Litigation Reform Act of 1995 and other Federal securities laws. Forward-looking statements contained in this press release include, but are not limited to, statements regarding Quantum X Labs’ and its subsidiaries’ strategic and business plans, technology, relationships, objectives and expectations for its business, growth, the impact of trends on and interest in its business, intellectual property, products and its future results, operations and financial performance and condition and may be identified by the use of words such as “may,” “seek,” “will,” “consider,” “likely,” “assume,” “estimate,” “expect,” “anticipate,” “intend,” “believe,” “do not believe,” “aim,” “predict,” “plan,” “project,” “continue,” “potential,” “guidance,” “objective,” “outlook,” “trends,” “future,” “could,” “would,” “should,” “target,” “on track” or their negatives or variations, and similar terminology and words of similar import, generally involve future or forward-looking statements. For example, the Company is using forward-looking statements when it discusses the continued development and optimization of its technologies, the expansion of its research and development activities, potential applications of its solutions, the advancement of its business strategy, and its expectations regarding future performance and growth opportunities. Forward-looking statements are not historical facts, and are based upon management’s current expectations, beliefs and projections, many of which, by their nature, are inherently uncertain. Such expectations, beliefs and projections are expressed in good faith. However, there can be no assurance that management’s expectations, beliefs and projections will be achieved, and actual results may differ materially from what is expressed in or indicated by the forward-looking statements. Forward-looking statements are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in the forward-looking statements. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s most recent Annual Report on 10-K and in subsequent filings with the SEC. Forward-looking statements speak only as of the date the statements are made. The Company assumes no obligation to update forward-looking statements to reflect actual results, subsequent events or circumstances, changes in assumptions or changes in other factors affecting forward-looking information except to the extent required by applicable securities laws. If the Company does update one or more forward-looking statements, no inference should be drawn that the Company will make additional updates with respect thereto or with respect to other forward-looking statements. References and links to websites have been provided as a convenience, and the information contained on such websites is not incorporated by reference into this press release. Quantum X Labs is not responsible for the content of third-party websites.
Investor Relations Contacts:
Michal Efraty
Investor Relations
michal@efraty.com
FAQ
AI-generated questions and answers. How Rhea-AI works. Not financial advice.
How much faster was Quantum X Labs' QXL gene-analysis benchmark with GPU acceleration?
The GPU-accelerated implementation achieved approximately 16.8-fold acceleration over the CPU-only implementation. Analysis took approximately 0.5 hours with a single NVIDIA T4 GPU, compared with approximately 8.4 hours using 64 vCPUs on the same machine. Both implementations produced the same qualifying gene-triplet results.
Did Quantum X Labs' gene-analysis benchmark establish clinical usefulness?
No clinical validity, predictive value or potential utility was established for the identified gene combinations. The benchmark was designed to evaluate computational performance using a real clinical gene-expression dataset comprising 11 patients and 3,531 features.
What computing setup did Quantum X Labs use for its quantum-simulation benchmark?
The benchmark used an AWS g4dn.16xlarge EC2 machine with IBM Qiskit Aer GPU-based quantum simulation and an NVIDIA T4 Tensor Core GPU. The machine had 64 x86_64 cores, and the comparison used the same machine with a CPU-only implementation.