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1153 systems 482 sites Sourced data

Supercomputers/Systems/Nabuchodonosor

France · operational · ai training

Nabuchodonosor

Also known as Scaleway Nabu 2023 AI supercomputer

Operated by Scaleway at Scaleway DC5 (Paris) .

Phase 1 seed dataset, compiled by hand. These rows were built from public operator, laboratory and vendor sources. A mechanical second-reader pass has since fetched every cited source: 1092 of 1153 systems have a readable citation that names them, and 40 are genuinely weakly sourced. Every claim carries its source and a confidence tier. Treat anything below verified as a lead, not a citation.

Measured performance

Rmax
-
Rpeak
-
Rmax ÷ Rpeak
-
Cores
-
Power
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Per watt
- GF/W

Figures are as last publicly reported for the configuration described below, not a live measurement. Where a system was upgraded in place, the post-upgrade configuration is shown and the earlier one appears in the timeline.

What this machine is made of

One row per supplier relationship. “Supplier at build” is the company that shipped the part at the time; where that company has since been acquired, the parent it rolls up to today is shown beside it. That distinction is what makes ticker-level aggregation possible across a thirty-year dataset.

Role Part Supplier at build Quantity Confidence Source
Accelerator NVIDIA H100 SXM5
Accelerators
CUDA (Hopper GH100) · 16,896C · 1.98 GHz · TSMC 4N · 700 W
127 NVIDIA DGX H100 systems with 1,016 H100 Hopper GPUs in a DGX SuperPOD
NVIDIA 1,016
verified
Verified scaleway.comnextplatform.com
Interconnect NVIDIA InfiniBand NDR (Quantum-2)
Interconnect
Fat tree or dragonfly+ · 400 Gb/s per port · Under 0.6 microseconds
NVIDIA Quantum-2 InfiniBand at 400 Gb/s in a non-blocking full fat tree, plus NVLink within each DGX
NVIDIA - Verified scaleway.comnextplatform.com
Storage -
DDN A3I storage cluster, 1.8 PB, 2.7 TB/s read and 1.95 TB/s write across the DGX nodes
DDN
- Reported nextplatform.com

AI datacenter metrics

Figures beyond an accelerator count, each with who stated it. What can and cannot be compared across AI datacenters.

MetricValueAs ofBasisNoteSource
Accelerators 1,016 accelerators 2023-10 Operator stated 127 DGX H100 systems, 1,016 H100 GPUs, per Scaleway. scaleway.com
PUE 1.25 2024-12 Operator stated Scaleway's 2024 PUE for DC5 (PAR2), the hosting data centre. Its custom-clusters page quotes 1.16 for the same site; the two do not agree. scaleway.comscaleway.com
WUE 0.25 L/kWh 2024-12 Operator stated Scaleway's 2024 WUE for DC5 (direct free cooling with adiabatic assist), the hosting data centre. scaleway.com

The read

Scaleway's first AI supercomputer, nicknamed Nabuchodonosor (a 15-litre champagne bottle), bought by Scaleway's telecom parent iliad Group and installed in the fall of 2023 in the Paris-based DC5 data center. An NVIDIA DGX SuperPOD of 127 DGX H100 systems with 1,016 H100 GPUs, linked by 400 Gb/s NVIDIA Quantum-2 InfiniBand in a non-blocking fat tree, with a DDN A3I storage cluster of 1.8 PB (Next Platform). Scaleway sells it as GPU cloud, with a 16-GPU Jeroboam variant launched alongside. Next Platform cites a vendor peak of over 4 exaflops at FP8 tensor precision, a low-precision AI rate that is not an HPL result, so no Rmax or Rpeak is recorded. DC5 is described as using adiabatic and outside-air cooling. Exact street location and power draw are not published.

Timeline

Site & facility

Scaleway DC5 (Paris)

Location
Paris, France
Cooling
Adiabatic and outside-air cooling
Commissioned
2023

Change history

Source check

We fetched this system's own citations and recorded whether each page actually mentions it. This is a corroboration signal, not a fact check, and it is published so you can see how well the sourcing holds up rather than take it on trust.

Cited sourceResultFound on the page
nextplatform.comnames system, part and countNVIDIA H100 SXM5, NVIDIA InfiniBand NDR (Quantum-2) · counts: 1016
scaleway.comnames system, part and countNVIDIA H100 SXM5, NVIDIA InfiniBand NDR (Quantum-2) · counts: 1016

Checked 2026-10-09 by pnpm verify. Re-run it and the table changes with the web.

Further reading