Intel Data Center GPU Max 1550C (Compute Module)

Intel Data Center GPU Max 1550C (Compute Module)

Brand: Intel | Category: GPUs

SKU: GPUMAX1550CXMR | Part #: GPUMAX1550CXMR | MPN: GPUMAX1550CXMR

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About the Intel Data Center GPU Max 1550C (Compute Module)

The Intel Data Center GPU Max 1550C is a Compute Module designed for high-performance AI and scientific computing workloads in enterprise data centers. Built on Intel's Xe HPC architecture (Ponte Vecchio), this accelerator delivers massive parallel processing capability through 128 Xe-cores, each equipped with 8 Vector Engines and 8 Matrix Engines for tensor operations. With 128 GB of HBM2e memory and 3.2 TB/s memory bandwidth, the GPUMAX1550CXMR excels at memory-intensive deep learning, simulation, and analytics tasks that demand both compute density and data throughput.

Intel's oneAPI software stack—including SYCL, OpenCL, oneDNN, and oneMKL—provides a unified programming framework across heterogeneous systems, simplifying deployment and optimization. The module features Intel Xe Link for peer-to-peer GPU communication, enabling multi-GPU scaling, and connects via PCIe 5.0 x16 through a dedicated module connector. With a 600 W TDP and fabricated using Intel 7 plus TSMC N5/N7 multi-tile heterogeneous packaging, this accelerator balances raw performance with power efficiency. AI infrastructure teams and HPC procurement professionals seeking enterprise-grade GPU compute for machine learning training, inference acceleration, and scientific computing will find the GPU Max 1550C a compelling addition to next-generation data center deployments. Contact Omnixon Global today to request a quotation for the Intel Data Center GPU Max 1550C.

Key Specifications

  • Manufacturer Part Number: GPUMAX1550CXMR
  • Architecture: Intel Xe HPC (Ponte Vecchio)
  • Memory Capacity: 128 GB HBM2e
  • Peak FP64 Vector Performance: 52.4 TFLOPS
  • Peak FP32 Performance: 104.8 TFLOPS
  • Memory Bandwidth: 3.2 TB/s
  • TDP: 600 W
  • PCIe Interface: PCIe 5.0 x16

Technical Specifications

BrandIntel
CategoryGPUs
SKUGPUMAX1550CXMR
Part NumberGPUMAX1550CXMR
ConditionNew
Manufacturer Part NumberGPUMAX1550CXMR
Product NameIntel Data Center GPU Max 1550C
Form FactorCompute Module
ArchitectureIntel Xe HPC (Ponte Vecchio)
Xe-cores128
Vector Engines per Xe-core8
Matrix Engines (XMX) per Xe-core8
Memory TypeHBM2e
Memory Capacity128 GB
Memory Bandwidth3.2 TB/s
Peak FP64 Vector Performance52.4 TFLOPS
Peak FP32 Performance104.8 TFLOPS
Peak BF16 Performance419.2 TOPS
Peak INT8 Performance838.4 TOPS
TDP600 W
Process TechnologyIntel 7 + TSMC N5/N7 (multi-tile, heterogeneous packaging)
InterconnectXe Link (peer GPU high-speed interconnect)
PCIe InterfacePCIe 5.0 x16 (host interface via module connector)
Software StackIntel oneAPI (SYCL, OpenCL, oneDNN, oneMKL)
OS SupportLinux (Red Hat Enterprise Linux, SUSE Linux Enterprise, Ubuntu LTS)

Frequently Asked Questions about Intel Data Center GPU Max 1550C (Compute Module)

What server platforms accept the Intel Data Center GPU Max 1550C (Compute Module)?

Reference servers include Dell PowerEdge XE9680 / XE9712, HPE Cray XD670, Lenovo ThinkSystem SR685a / SR675 V3, Supermicro AS-A21GE / SYS-821GE, Gigabyte G593 / G894, ASUS ESC. Share your target platform in the RFQ and we will confirm chassis-to-GPU compatibility and recommended NIC pairing.

How long is the lead time on AI GPUs?

Highly model-dependent. L40S / RTX-class: typically 3-6 weeks. H100/H200/B200 in SXM form factor: 12-16 weeks for whole-platform allocations. We quote genuine-channel ETAs only — no grey-market promises.

Do you supply matched networking (Quantum InfiniBand / Spectrum-X)?

Yes — Omnixon stocks the full NVIDIA networking lineup (Quantum-2 / Quantum-X InfiniBand, Spectrum-X Ethernet, ConnectX NICs, BlueField DPUs) so we can quote a complete training-cluster BOM, not just the GPUs.

Can you help with NVIDIA AI Enterprise licensing?

Yes. We hold genuine-channels for NVIDIA AI Enterprise software subscriptions. Add it to your RFQ and we quote node-aligned licensing along with the hardware.