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What did Dutch quantum-control company Qblox announce in Delft on October 22, 2026, about connecting NVIDIA’s DGX Spark desktop AI system to its quantum controller through NVQLink, what round-trip latencies did it measure on DGX Spark and the RTX PRO 6000 Blackwell GPU, how do it
Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum-system controller through NVQLink, bringing GPU acceleration into real-time hybrid quantum–classical control. Its reported round-trip latencies were below 7.2 microseconds on DGX Spark and below 4.0 m Qblox announced...
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Key takeaways
- Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum-system controller through NVQLink, bringing GPU acceleration into real-time hybrid quantum–classical control. Its reported round-trip latencies were below 7.2 microseconds on DGX Spark and below 4.0 m
- Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum-system controller through NVQLink, bringing GPU acceleration into real-time hybrid quantum–classical control. Its reported round-trip latencies were below 7.2 microseconds on DGX S
- ## What the integration establishes
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openai.comCreate a landscape editorial hero image for this Studio Global article: What did Dutch quantum control company Qblox announce in Delft on October 22, 2026, about connecting NVIDIA’s DGX Spark desktop AI system to. Article summary: Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum system controller through NVQLink, bringing GPU acceleration into real time hybrid quantum–classical control.. Topic tags: general web, ai, automation, workflow, code. Style: premium digital editorial illustration, source-backed research mood, clean composition, high detail, modern web publication hero. Use reference image context only for broad subject, composition, and topical grounding; do not copy the exact image. Avoid: logos, brand marks, copyrighted characters, real person likenesses, fake screenshots, UI text, readable text, watermarks, charts with fake n
Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum-system controller through NVQLink, bringing GPU acceleration into real-time hybrid quantum–classical control. Its reported round-trip latencies were below 7.2 microseconds on DGX Spark and below 4.0 microseconds on the RTX PRO 6000 Blackwell GPU—not below 4.0 microseconds on both systems. 7
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What the integration establishes
- Measured latency: Qblox’s own announcement distinguishes the two hardware results; it is more reliable for these numbers than the abbreviated secondary summary that appears to apply the sub-4-microsecond result to both platforms.
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- Q1 and LINQ feedback: Qblox documents sharing Q1 registers and immediate values, and sharing measurement results through LINQ-based feedback.
4 LINQ carries thresholded bits, IQ values, time-tags and registers between sequencers in real time, with latency depending on routing, payload type and size.
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- CUDA-Q foundation: Qblox’s March 16, 2026 announcement said it supported public availability of NVQLink through the
cudaq-realtimeAPI, building on its collaboration announced in October 2025.
Insufficient evidence: the available excerpts do not establish the precise mechanism for combined quantum, AI and simulation workloads, calibration during an experiment, GPU-based decoding in this particular Qblox setup, or unchanged-code migration to data-center GPUs. They also do not contain Niels Bultink’s or Sam Stanwyck’s remarks, so I cannot reliably attribute their specific scaling arguments.
NVQLink background and logical-qubit relevance
- Launch and ecosystem: The available evidence dates NVQLink’s introduction to October 28, 2025, describes it as an open interconnect between quantum processors and GPU supercomputers, and lists 17 QPU builders, five control-system builders and nine U.S. national laboratories; named builders include IonQ, Quantinuum, Oxford Quantum Circuits and ORCA Computing.
6 A participant’s retrospective places the launch at GTC Washington, D.C.
- Architecture: NVIDIA describes a logical-QPU machine model consisting of a real-time accelerated-computing host and quantum-system controller joined by a scalable, low-latency interconnect for fault-tolerant runtime workloads.
- Demonstrated error correction: NVIDIA reported that Quantinuum’s Helios QPU, connected to a GH200 Grace Hopper real-time host, used the CUDA-Q QEC library’s
nv-qldpc-decoderfor real-time quantum low-density parity-check decoding and achieved a 5.4-fold improvement in logical-qubit error rate.
Insufficient evidence: the supplied excerpts do not verify the complete supported-host list or the exact sub-4.0-microsecond FPGA-to-GPU-to-FPGA specification. Qblox’s measured hardware latencies should therefore not be treated as verification of that separate architectural specification.
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What is the short answer to "What did Dutch quantum-control company Qblox announce in Delft on October 22, 2026, about connecting NVIDIA’s DGX Spark desktop AI system to its quantum controller through NVQLink, what round-trip latencies did it measure on DGX Spark and the RTX PRO 6000 Blackwell GPU, how do it"?
Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum-system controller through NVQLink, bringing GPU acceleration into real-time hybrid quantum–classical control. Its reported round-trip latencies were below 7.2 microseconds on DGX Spark and below 4.0 m
What are the key points to validate first?
Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum-system controller through NVQLink, bringing GPU acceleration into real-time hybrid quantum–classical control. Its reported round-trip latencies were below 7.2 microseconds on DGX Spark and below 4.0 m Qblox announced in Delft on October 22, 2026, that it had connected NVIDIA DGX Spark to its quantum-system controller through NVQLink, bringing GPU acceleration into real-time hybrid quantum–classical control. Its reported round-trip latencies were below 7.2 microseconds on DGX S
What should I do next in practice?
## What the integration establishes