Postquant Labs has launched its Quip Virtual Machine (QVM), a shared programming environment designed to run on leading quantum hardware platforms. In a demonstration at Quantum Tech World, the QVM ran 1,930 portfolio optimization tests, with quantum solvers matching or exceeding the performance of classical solvers in every instance where the difference exceeded 0.5%.
Colton Dillion, CEO and Co-Founder of Postquant Labs, said, “We created the QVM because quantum computing is still fragmented between competing instruction sets and assemblers, providing few easy onramps for newcomers.” Researchers from Monash University, the University of Notre Dame, and Purdue University are currently evaluating the QVM, while SiC Systems is exploring its use in industrial optimization, including AI-driven manufacturing and chemical process control.
Quip Virtual Machine Unifies Quantum and Classical Execution
The Quip Virtual Machine (QVM) establishes a unified cost model for quantum computation, assigning value to qubit space, execution time and entanglement. This feature addresses a critical barrier to wider adoption. This gas-based system predicts maximum computational cost before execution, allowing businesses to budget for quantum workloads with the same predictability as traditional cloud computing resources. Unlike existing quantum cloud offerings that often require substantial upfront commitments or vendor-specific pricing structures, the QVM quotes a maximum cost in compute credits for each transaction, mirroring the metered model of AWS Braket but with upfront, spot-style pricing.
Dr. Terrence Mak, Professor in the Department of Data Science & AI at Monash University, explained that students often spend an entire semester learning how to program using the latest quantum paradigms. As they evaluate Quip’s virtual machine, he believes it can speed up student training and give them more time for research instead of learning a specific programming language or how to program quantum circuits. This emphasis on reducing the learning curve highlights a key goal of the QVM: to lower the barrier to entry for those seeking to explore quantum computing.
SiC Systems is actively exploring the QVM to tackle industrial optimization challenges in areas like AI-driven manufacturing and the control of complex chemical and biological processes, the company says. “At SiC Systems, we face a variety of combinatorial optimization problems, and time is of the essence. We want to explore as many solutions as possible in as short a time as possible. This is particularly important in our physics-informed agent architecture to design, control and operate complex chemical and biological manufacturing processes.
Quip Network’s QVM can help us meet that requirement and better serve our customers,” said Dr. Soheil Mansouri, Co-Founder and Chief Science Officer at SiC Systems. This application extends beyond purely computational research, indicating a focus on practical, real-world implementations of quantum computing. The QVM’s architecture, modeled after Ethereum’s Virtual Machine, allows developers to write programs in a single constraint-based language compatible with annealers, gate-based quantum systems and classical hardware.
These programs compile into quantum or classical instructions with predetermined costs, deploying to the Quip Network and running on connected quantum computers. Classical machines then benchmark and validate the outputs, and developers can publish programs publicly, earning payment each time they are executed. This system is underpinned by a three-tier verification process. Quantum outputs are cross-checked against classical simulations, classical providers independently benchmark results, and cryptographic attestations bind each result to the hardware that produced it. Disputes over faulty results are resolved against recorded benchmarks, rather than relying on self-reporting from operators.
A gas-based cost model is the missing piece that demonstrates quantum computing is commercially viable and practical. When you can predict exactly what a computation will cost before you run it, quantum tests that began as a research experiment become a real tool for engineering because you can quantify exactly how much value it can bring to your products. This is the shift we will be delivering.” The QVM is currently live on the Aglais testnet, with free compute credits available for new users, and will transition to mainnet pricing in network tokens.
Using a pay-as-you-go “gas-based” cost model is the missing piece that demonstrates quantum computing is commercially viable and practical.
Dr. Richard Carback, chief technology officer and co-founder of Postquant Labs
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