The quantum computing market in Russia is transitioning from experimental prototypes to the delivery of fully functional computing systems. Quantum Park of the Federal State Unitary Enterprise (FSUE) VNIIA and Bauman Moscow State Technical University announced the start of sales of their first line of high-precision superconducting quantum computers, which are based on the SnowDrop architecture, on September 15, 2026. Customers have the option to purchase one of four models, which range from four to ten qubits. The offering includes a comprehensive hardware and software platform.
A Quantum Computer as a Complete System
The main feature of the new offering is that customers do not need to build the infrastructure surrounding the quantum processor themselves. The system comprises a SnowDrop superconducting quantum coprocessor, a qubit readout system, a YARANGA ultralow-temperature cryostat with signal-switching equipment, control electronics, and a software environment for the development and execution of quantum algorithms.
This approach differs fundamentally from supplying an experimental quantum chip on its own. The quantum processor is just one component of a much more intricate system, as superconducting qubits must operate at temperatures as low as a few tens of millikelvin. The Russian YARANGA dilution cryostats operate at temperatures below 20 mK, as per the developers.
The starting price for the scalable cryogenic platform equipped with the four-qubit SnowDrop 4Q and a quantum readout system is from RUB 170 million.
Four SnowDrop Versions
The quantum coprocessor is available in four different versions within the product line. SnowDrop 4QTCS and SnowDrop 8Q2TCS implement a T-shaped connectivity architecture, whereas SnowDrop 8QGCL and SnowDrop 10QGCL implement a grid-based connectivity architecture. The latter two solutions are intended to facilitate additional system scaling, according to the developers.
The number of qubits, however, is not the only important parameter. The accuracy of operations, qubit stability, readout quality, and the capacity to scale the architecture are all essential for practical quantum computing.
SnowDrop quantum chips use transmon qubits that are frequency-tunable and have coupling elements that are individually controlled. Additionally, the developers assert that they have developed patented technologies that enable the execution of high-fidelity two-qubit operations. Single-qubit operation errors are specified to be no more than 0.2% on the production line, while two-qubit operation errors are no more than 1%. The architecture also includes simplified calibration procedures.
From Cloud Experiments to Quantum Hardware Sales
The current launch represents the next stage of a project that has already been subjected to testing on a cloud-based infrastructure. Users from five countries evaluated the SnowDrop architecture on the Bauman Octillion platform, which was made publicly accessible in 2025. This provided the developers with the opportunity to operate SnowDrop quantum processors not only in laboratory settings, but also through remote access by external users.
Since July 2025, the SnowDrop 4Q and SnowDrop 8Q systems have been used to execute over 103,000 hybrid quantum-classical algorithms on the Bauman Octillion, according to Bauman Moscow State Technical University. The quantum-classical system’s cumulative continuous operational time exceeded 9,000 hours.
Development of the platform continued in 2026. Bauman Octillion users were granted access to a new eight-qubit SnowDrop 8Q for experimentation in August. The developers reported a two-qubit operation fidelity of up to 99.55% for specific pairs of connected qubits, and experimental results suggested that the figure could be increased to over 99.9%.
Possible Applications of Russian Quantum Computers
According to the developers, SnowDrop is primarily intended as a platform for applied tasks and research. Artificial intelligence and machine learning, financial analytics, drug and chemical compound development, cybersecurity, and the optimization of energy systems and logistics routes are all potential applications.
These machines cannot be considered direct counterparts for classical supercomputers at the current qubit count. Their objective is considerably more specialized: They focus on developing and testing quantum algorithms, simulating quantum systems and materials, investigating optimization methods, and preparing software for future, more powerful quantum machines.
This implies that SnowDrop will be predominantly utilized as a research platform by the first customers. It offers an opportunity for industry to establish in-house quantum computing expertise, rather than relying solely on experiments conducted through cloud services.
A Focus on Scalability
The developers underscore that the existing 4–10-qubit systems are the initial phase of a scalable architecture. The SnowDrop 8QGCL and 10QGCL models employ new materials, technologies that are intended to improve coherence, and architectural solutions that are specifically designed to accommodate additional qubit expansions.
This is especially crucial in quantum computing, where the mere increase in the number of qubits does not necessarily result in improved practical computing performance. The control of errors, interactions between qubits, readout processes, and the stability of the entire computational chain becomes more challenging as systems expand.
Due to this, the development of a comprehensive domestic hardware and software stack—including the superconducting chip, cryogenic system, control electronics, and software—may be crucial for future scalability.
Quantum Hardware for Universities, Business Expertise
The availability of commercially supplied systems presents an opportunity for universities and research centers to conduct experiments directly on actual superconducting quantum hardware and train students to work with quantum systems. This is especially pertinent in light of the fact that Russia is currently in the process of establishing new educational programs in quantum technologies.
Businesses have the opportunity to develop quantum-classical algorithms internally, establish specialist teams, and evaluate specific application scenarios by purchasing such a system prior to the availability of larger-scale quantum computers.