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Los Alamos National Laboratory has selected NVIDIA Vera CPUs and the Vera Rubin platform for three planned supercomputers: Mission, Vision, and Veritas. HPE will build the systems using HPE Cray architecture. The announcement describes a future deployment, not a confirmed arrival: DOE/NNSA said a first Vera Rubin test server was expected at LANL in summer 2026, but the official sources reviewed do not confirm that it arrived.
What LANL announced
The plan pairs NVIDIA Vera CPUs and Rubin GPUs with Quantum-X800 InfiniBand networking in systems built by HPE on HPE Cray supercomputing architecture. NVIDIA identifies the architecture as HPE Cray Supercomputing GX5000. The three systems are designed for different kinds of national-laboratory work rather than as interchangeable machines.
The named systems are Mission, Vision, and Veritas. DOE/NNSA’s July 16, 2026 announcement covers Mission and Vision; NVIDIA’s June 22 announcement also describes Veritas. Their purposes and schedules should be read separately.
How the three systems differ
| System | Intended work | Published planned configuration | Schedule information |
|---|---|---|---|
| Mission | Classified national-security workloads; NVIDIA says it is intended to replace Crossroads. | NVIDIA reports Vera Rubin GPU nodes and 2,300 standalone Vera CPUs using an HPE Cray GX240 blade. This is a vendor-stated planned configuration, not a verified final inventory. | NVIDIA said it was expected to be operational in 2027. DOE/NNSA gives a 2027–2028 full-deployment window for Mission and Vision together, without assigning a year to each. |
| Vision | Open and fundamental science, including AI, materials and nuclear science, energy modeling, biomedical research, fusion, and quantum computing. | A standalone Vera CPU count is not stated in the reviewed NVIDIA LANL-focused announcement. | DOE/NNSA’s combined full-deployment expectation for Mission and Vision is 2027–2028; it does not specify which year applies to Vision. |
| Veritas | LANL’s Laboratory Directed Research and Development (LDRD) work, scientific discovery, and testing agentic-AI technologies for potential use in larger systems. | NVIDIA reports Rubin GPU nodes and approximately 1,150 standalone Vera CPUs. This is a planned, vendor-reported configuration. | A deployment date is not stated in the cited DOE/NNSA announcement, which discusses Mission and Vision. |
NVIDIA’s June 22, 2026 announcement describes the system selection and scientific roles. Its LANL-focused Vera CPU blog provides the planned standalone CPU counts and vendor-reported workload comparisons. DOE/NNSA’s July 16 announcement covers the partnership and Mission/Vision timing.
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Has the first Vera server arrived?
That is not confirmed by the cited official material. DOE/NNSA said a first Vera Rubin CPU server was expected to arrive at LANL in summer 2026 for testing. An expected arrival is not evidence that delivery or testing occurred, and the announcement of the three systems does not establish that any is operational.
The schedule language also differs by source. DOE/NNSA projects full deployment of Mission and Vision in 2027 and 2028 but does not assign a specific year to each system. NVIDIA separately said Mission and Vision were expected to be operational in 2027. These are projections with different wording, not confirmation of completed deployment.
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What the performance figures do—and do not—show
NVIDIA reports that LANL demonstrated up to seven times higher performance on URSA workloads than the CPUs in Crossroads. That is a comparison for the named workloads, not a general-purpose benchmark or a measured result for a completed Mission system. NVIDIA also reports more than three times the performance versus Crossroads CPUs on Branson, an early test involving the open-source Monte Carlo heat-transfer simulation tool.
Separately, NVIDIA makes broad product comparisons for Vera: more than three times the performance versus a single-socket x86-based CPU, more than four times the memory per core, and six times the memory per node. These are vendor claims and should not be conflated with the workload-specific LANL demonstrations or system-wide results from deployed supercomputers.
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NVIDIA’s Vera CPU product page lists 88 custom Olympus cores, up to 1.2 terabytes per second of LPDDR5X memory bandwidth, and up to 1.5 TB of memory. Those are product-level specifications, not proof that every LANL node will use those exact memory configurations or achieve those figures in practice.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why LANL is using separate systems
The division of roles reflects distinct operating needs. Mission is for classified national-security work; Vision is intended for open scientific research; and Veritas is an LDRD-focused environment for exploring technologies that could inform larger systems. NVIDIA presents the Vera CPU as relevant to workloads that benefit from high memory bandwidth and CPU capacity alongside GPU computing, while Rubin GPUs and high-speed networking form part of the broader platform.
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In DOE/NNSA’s July announcement, LANL chief architect of advanced technology systems Galen Shipman said the design emphasis on high-memory bandwidth and complex applications improved performance and efficiency for challenging workloads. That is an official’s characterization of the design and reported work, not an independent system-wide benchmark. NNSA Administrator Brandon Williams described the partnership as supporting the Genesis Mission and said the aim was to reduce discovery timelines from months to minutes; that phrase is an objective, not a measured outcome.
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- Cooler not included
What remains unknown
- Whether the anticipated summer 2026 test server actually arrived and completed testing.
- Final delivered configurations, including a published standalone Vera CPU count for Vision.
- Confirmed operational dates, especially a system-specific deployment year for Mission versus Vision.
- System-wide performance after deployment, realized energy savings, and project costs.
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