Brand: Intel | Category: GPUs
SKU: GPUMX1100CXAAA | Part #: GPUMX1100CXAAA | MPN: GPUMX1100CXAAA
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The Intel Data Center GPU Max 1100C is a high-performance discrete GPU built on Intel's Ponte Vecchio architecture, utilizing the Xe HPC microarchitecture designed specifically for demanding data center, HPC, and AI inference workloads. Fabricated using a multi-tile design with TSMC and Intel process nodes, the GPU Max 1100C delivers substantial compute throughput across FP64, FP32, BF16, and INT8 precisions, making it well-suited for scientific simulation, machine learning training, and large-scale data analytics pipelines.
The 1100C variant is the water-cooled form factor of the Intel GPU Max 1100 series, enabling higher sustained thermal performance in dense rack deployments where airflow is constrained. It connects to host systems via a PCIe Gen 5 x16 interface and exposes a unified, large-capacity HBM2e memory subsystem that provides high bandwidth for memory-bound workloads common in computational chemistry, climate modeling, and transformer-based AI models.
Programmability is delivered through Intel's oneAPI toolkit, which supports SYCL, OpenMP offload, and provides migration paths from CUDA-based codebases via the Intel DPC++ Compatibility Tool. The GPU Max 1100C integrates with Intel's software ecosystem across MPI-based HPC frameworks and popular AI frameworks including TensorFlow and PyTorch, enabling organizations to deploy it within existing enterprise and supercomputing software stacks with minimal rework.
| Manufacturer | Intel |
| Manufacturer Part Number | GPUMX1100CXAAA |
| Product Family | Intel Data Center GPU Max Series |
| Architecture | Xe HPC (Ponte Vecchio) |
| Form Factor | OAM (OCP Accelerator Module) — liquid-cooled (1100C variant) |
| Cooling Solution | Water / liquid cooling |
| Host Interface | PCIe Gen 5 x16 |
| Xe-cores | 56 |
| Vector Engines per Xe-core | 8 |
| Matrix Engines per Xe-core | 8 |
| Memory Type | HBM2e |
| Memory Capacity | 48 GB |
| Memory Bandwidth | Up to 1.229 TB/s |
| FP64 Vector Performance | Up to 22.22 TFLOPS |
| FP32 Vector Performance | Up to 22.22 TFLOPS |
| BF16 Matrix Performance | Up to 444 TOPS |
| INT8 Matrix Performance | Up to 888 TOPS |
| TDP (Thermal Design Power) | Up to 600 W |
| Programming Model | oneAPI (SYCL, OpenMP offload, DPC++) |
| Supported AI Frameworks | TensorFlow, PyTorch (via Intel Extension for PyTorch) |
| Target Deployment | Data center HPC, AI training and inference, liquid-cooled dense rack |
Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.
| Brand | Intel |
| Category | GPUs |
| SKU | GPUMX1100CXAAA |
| Part Number | GPUMX1100CXAAA |
| Condition | New |
| Manufacturer Part Number | GPUMX1100CXAAA |
| Product Family | Intel Data Center GPU Max Series |
| Architecture | Xe HPC (Ponte Vecchio) |
| Form Factor | OAM (OCP Accelerator Module) — liquid-cooled (1100C variant) |
| Cooling Solution | Water / liquid cooling |
| Host Interface | PCIe Gen 5 x16 |
| Xe-cores | 56 |
| Vector Engines per Xe-core | 8 |
| Matrix Engines per Xe-core | 8 |
| Memory Type | HBM2e |
| Memory Capacity | 48 GB |
| Memory Bandwidth | Up to 1.229 TB/s |
| FP64 Vector Performance | Up to 22.22 TFLOPS |
| FP32 Vector Performance | Up to 22.22 TFLOPS |
| BF16 Matrix Performance | Up to 444 TOPS |
| INT8 Matrix Performance | Up to 888 TOPS |
| TDP (Thermal Design Power) | Up to 600 W |
| Programming Model | oneAPI (SYCL, OpenMP offload, DPC++) |
| Supported AI Frameworks | TensorFlow, PyTorch (via Intel Extension for PyTorch) |
| Target Deployment | Data center HPC, AI training and inference, liquid-cooled dense rack |
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.
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.
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.
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.