Gigabyte 8 GPU Servers for Enterprise AI Workloads

When it comes to enterprise AI infrastructure, the server platform around a GPU matters as much as the GPU itself. CPU architecture, memory capacity, storage bandwidth, cooling design, and expansion flexibility all determine how well a system performs under sustained AI workloads. Gigabyte has built a strong portfolio of 8 GPU server platforms across multiple GPU generations and CPU architectures, purpose-built for the demands of AI training, inference, and high-performance computing.

This guide covers the Gigabyte 8 GPU server lineup available through Saitech, how each platform is configured, what workloads it is suited for, and how to make the right selection for your enterprise AI deployment.

Why Gigabyte for Enterprise AI Infrastructure?

Gigabyte has been a trusted provider of enterprise server hardware for decades. Their GPU server line, developed under the Giga Computing brand for the server division, is designed specifically for high-density compute environments where reliability and sustained performance under load are non-negotiable requirements.

What sets Gigabyte's 8 GPU server platforms apart in the enterprise AI context is the range of configurations they support.

The same chassis design philosophy spans multiple GPU generations, from NVIDIA HGX H200 and B200 to B300, and extends to AMD Instinct and Intel Gaudi accelerators.

That flexibility means organizations standardizing on Gigabyte platforms can evolve their GPU infrastructure generationally without re-architecting everything around a new system design each time.

Gigabyte 8 GPU servers are available through Saitech, an authorized Gigabyte reseller, with configurations based on Intel Xeon and AMD EPYC processors to support a wide range of enterprise AI deployments.

The G893 Series: Gigabyte's Air-Cooled 8 GPU Platform

The Gigabyte G893 GPU Server Series, launched in January 2025, is the current flagship multi-GPU platform for organizations that need 8 GPU density without liquid cooling infrastructure. It is an 8U air-cooled design that supports NVIDIA HGX B200, AMD Instinct MI325X, and Intel Gaudi 3 accelerators, which makes it one of the more GPU-agnostic 8 GPU server platforms on the market. The air-cooled design is the G893's key practical advantage for many enterprise deployments. Liquid cooling infrastructure, cooling distribution units, and modified rack configurations add significant complexity and upfront cost to data center operations. The G893 delivers 8 GPU compute density without requiring any of that, which makes it a realistic option for enterprise data centers that have not yet invested in liquid cooling and need HGX-class GPU density on existing infrastructure.

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This Intel Xeon-based configuration supports dual 4th or 5th Gen Intel Xeon Scalable processors with up to 350W TDP and 32 DIMM slots supporting up to 2 TB of DDR5 memory. It uses the NVIDIA HGX B200 modular GPU platform and is designed for AI training, HPC, and large-scale inference workloads. The 32-slot memory configuration provides headroom for large data preprocessing pipelines and multi-model inference environments where system memory matters as much as GPU memory.

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The AMD EPYC variant of the G893 supports dual AMD EPYC 9005 or 9004 Series processors with the same 8U form factor. EPYC's higher core counts and memory bandwidth characteristics make this configuration well-suited for workloads where the data pipeline between storage, CPU, and GPU is as demanding as the GPU compute itself. Available through Saitech for organizations standardized on the AMD EPYC ecosystem.

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This configuration supports eight AMD Instinct MI350X OAM GPUs with dual AMD EPYC processors and DDR5 memory. It is aimed at organizations running ROCm-based AI workloads or those evaluating AMD's GPU stack as an alternative to NVIDIA for training and inference. For teams with AI frameworks already optimized for AMD hardware, the all-AMD system design of the G893-ZX1-AAX3 eliminates cross-vendor compatibility considerations.

The full G893 series is covered in more technical depth in the GIGABYTE G893 GPU Servers guide on the Saitech blog.

G893 Series: Configuration Comparison

Comparing Gigabyte 8 GPU Server Generations

Matching Gigabyte 8 GPU Configurations to Workloads 

For LLM Training at 7B to 70B Parameters 

The G893 with HGX B200 and the G593 with HGX H200 are both well suited for training LLMs in this parameter range. The B200 delivers meaningfully more GPU memory per card and higher interconnect bandwidth, which improves throughput on models at the upper end of this range. The air-cooled G893 design makes it the more accessible deployment option for data centers without liquid cooling. For teams prioritizing memory headroom alongside training compute, the G593 with its 6 TB system memory ceiling is worth evaluating. 

For Production Inference Serving 

8 GPU configurations excel at inference serving because the full model can reside in the combined GPU memory pool across all eight cards. On a G893 with HGX B200, the 1.44 TB GPU memory pool is sufficient to serve models up to approximately 200B to 250B parameters in FP8 precision without model parallelism across nodes. The G894 with HGX B300 extends that to approximately 400B to 500B parameters in FP4 precision, alongside B300's 2x attention performance advantage that directly improves tokens-per-second throughput. 

For Multi-GPU Clusters 

All Gigabyte 8 GPU server platforms with HGX modules include NVLink and NVSwitch interconnects for intra-node communication and support InfiniBand or high-speed Ethernet for multi-node cluster fabric.  

The G894's ConnectX-8 SuperNICs with 800 Gb/s InfiniBand are the highest-bandwidth option for organizations building multi-node B300 clusters where inter-node gradient synchronization latency matters. For H200-based clusters, the G593 series supports NVIDIA BlueField-3 DPUs for SmartNIC capabilities alongside standard InfiniBand connectivity. 

For a detailed look at how multi-GPU server configurations fit into broader GPU cluster design, the Why NVIDIA HGX B200 Servers Are Ideal for Large-Scale AI Training guide covers multi-node networking, InfiniBand fabric design, and cluster scaling considerations that apply directly to B300 cluster planning decisions. 

For HPC and Scientific Workloads 

Gigabyte's multi-accelerator support is particularly relevant for HPC environments that run mixed workloads. The G893 series supports NVIDIA, AMD, and Intel accelerators within the same chassis platform, which allows organizations to standardize on Gigabyte hardware while maintaining flexibility on GPU vendor selection based on software stack and workload requirements. 

Data Center Requirements for Gigabyte 8 GPU Servers 

Planning AI compute infrastructure around Gigabyte 8 GPU servers requires confirming three data center readiness factors before procurement: power capacity, cooling availability, and rack space. Each varies meaningfully across the G893 and G894 platform generations. 

Power 

The G893 air-cooled series is built around six 3 kW Titanium-rated power supplies, with total system draw at full GPU load in the 14 to 16 kW range depending on processor and GPU configuration. The G894 with HGX B300 requires twelve 3 kW PSUs given the higher TDP of Blackwell Ultra GPUs, bringing full-load draw to 18 kW or above. Per-rack power capacity must be confirmed before deployment. 

Cooling 

The G893 handles thermal management through air cooling, which is its key advantage for standard data center deployments. The G594 and G893 HGX H200 platforms require liquid cooling given HGX SXM GPU thermal density. Organizations planning G894 B300 deployments must have liquid cooling infrastructure available, as air cooling is not rated for sustained Blackwell Ultra workloads. 

Rack Space 

All flagship Gigabyte 8 GPU server configurations use an 8U form factor. At standard rack depths, this means four 8U systems per 42U rack alongside networking, storage, and management hardware. 

Saitech's storage server solutions complement Gigabyte GPU server deployments with NVMe and parallel storage configurations sized to keep 8 GPU systems fully fed without I/O bottlenecks during training. 

Why Buy Gigabyte 8 GPU Servers Through Saitech? 

Saitech is an authorized Gigabyte reseller and NVIDIA Preferred Partner. That combination matters for HGX-based configurations specifically. Authorized channel access ensures systems arrive with genuine, warranted hardware and OEM support eligibility. As an NVIDIA Preferred Partner, Saitech has access to NVIDIA technical resources that help support complex deployment planning, which is particularly valuable when configuring multi GPU servers for large-scale AI training or multi-node cluster deployments. 

Gigabyte GPU servers are stocked and configurable to order. Most configurations ship within 24 to 48 business hours. For HGX-based systems requiring pre-staging and full-stack software configuration, lead times are confirmed at order. TAA-compliant configurations are available for federal and defense buyers. 

Conclusion 

Gigabyte's 8 GPU server portfolio covers the full range of enterprise AI infrastructure requirements: from air-cooled B200 platforms that deploy on existing data center infrastructure to liquid-cooled HGX B300 systems built for the most demanding frontier AI workloads. With Intel Xeon and AMD EPYC options across the lineup and support for NVIDIA, AMD, and Intel GPU architectures, Gigabyte gives enterprise buyers real flexibility without sacrificing the density and interconnect performance that serious AI workloads demand. 

Saitech Inc. has been delivering enterprise AI and HPC infrastructure since 2002. As an authorized Gigabyte reseller and NVIDIA Preferred Partner, Saitech configures, validates, and deploys Gigabyte 8 GPU servers built for the training, inference, and HPC workloads enterprises are running today.