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AMD MI300X GPU: Massive Memory Meets Open AI Compute

The AMD Instinct MI300X is a data center accelerator purpose-built for generative AI, large language model (LLM) inference, and high-performance computing. Built on AMD's CDNA 3 chiplet architecture, the MI300X pairs 192GB of HBM3 memory with 5.3 TB/s of aggregate memory bandwidth — the largest memory footprint of any single GPU accelerator in its class.

That memory capacity changes what's possible on one GPU. A 70-billion-parameter model that needs two or more NVIDIA H100s to fit in memory runs comfortably on a single MI300X, with headroom left for KV cache and larger batch sizes. For inference-heavy workloads, that translates directly into fewer GPUs per model, lower cross-GPU communication overhead, and a lower cost per query.

As an AMD MI300X GPU server on Cyfuture AI's cloud, it's available as on-demand GPU as a Service — no upfront hardware investment, no long procurement cycles. You get enterprise-grade AI infrastructure with 99.9% uptime, rapid provisioning, and 24/7 expert support, so your models move from experiment to production faster.

AMD MI300X GPU Server — Instance Options

Scalable MI300X configurations, from a single accelerator to a full 8-GPU node with 1.5TB of pooled HBM3 memory.

Dollar INR
Instance Name Compute unit Model AI Compute memory (GB) Performa FP32 Performa FP16 vCPU Instance memory(GB) Peer to Peer Bandwidth (GB/s) Network Bandwidth (GB/s) Peak/Benchmark Memory Bandwidth (GB/s) On Demand Price/hour 1 Month Reserved Price/hr 6 Month Reserved Price/hr 12 Month Reserved Price/hr Action
1MI300.16v.256m AMD 1xMI300X (1X) 192 163 1307 16 256 - 400 580

₹ 274

₹ 219


(20.08% Discount)

₹ 197


(28.11% Discount)

₹ 164


(40.16% Discount) 		Reserve Now
2MI300.32v.512m AMD 2xMI300X (2X) 384 326 2614 32 512 900 800 580

₹ 542

₹ 429


(20.89% Discount)

₹ 382


(29.56% Discount)

₹ 315


(41.98% Discount) 		Reserve Now
4MI300.64v.1024m AMD 4xMI300X (4X) 768 652 5228 64 768 1800 1600 580

₹ 1074

₹ 849


(20.90% Discount)

₹ 756


(29.57% Discount)

₹ 623


(41.99% Discount) 		Reserve Now
8MI300.128v.2048m AMD 8xMI300X (8X) 1536 1304 10456 128 1536 3600 3200 580

₹ 2125

₹ 1681


(20.91% Discount)

₹ 1496


(29.59% Discount)

₹ 1233


(42.02% Discount) 		Reserve Now

Ready to Run Large-Memory
AI Workloads?

Rent AMD MI300X GPU capacity on Cyfuture AI's cloud today and get 192GB of HBM3 memory working for your models.

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Features & Benefits

Industry-Leading 192GB HBM3 Memory
Industry-Leading 192GB HBM3 Memory

With 192GB of high-bandwidth memory per GPU — roughly 2.4x an NVIDIA H100's 80GB — the MI300X lets you load larger models, longer context windows, and bigger batches on fewer accelerators. This is the single biggest reason enterprises rent MI300X cloud GPU capacity for memory-bound inference workloads.

5.3 TB/s Memory Bandwidth
5.3 TB/s Memory Bandwidth

Eight HBM3 stacks feed data to AMD's CDNA 3 compute dies at up to 5.3 TB/s aggregate bandwidth, keeping 304 compute units and 1,216 matrix cores fed for transformer-heavy, bandwidth-bound workloads like attention layers and embedding lookups.

Chiplet Architecture Built for Scale
Chiplet Architecture Built for Scale

The MI300X integrates 8 XCD compute dies and 4 I/O dies on a single package using AMD's Infinity Fabric interconnect. This chiplet design lets AMD scale compute and memory independently, improving yield and giving each MI300X a large 256MB Infinity Cache to reduce off-chip memory traffic.

Open Software Stack with ROCm
Open Software Stack with ROCm

The MI300X runs on AMD's open-source ROCm platform with native support for PyTorch, TensorFlow, JAX, and ONNX Runtime. HIP tooling helps port existing CUDA code, giving teams that want to avoid single-vendor lock-in a fully supported alternative path for training and inference.

Enterprise Multi-GPU Scaling
Enterprise Multi-GPU Scaling

On an 8-GPU Universal Baseboard (UBB) configuration, MI300X accelerators connect via 4th-generation Infinity Fabric for up to 896 GB/s of aggregate peer-to-peer bandwidth, pooling 1.5TB of HBM3 memory across the node for large distributed training and multi-instance inference.

AMD MI300X — Technical Specifications

Specification Details
Architecture & Manufacturing
GPU Architecture AMD CDNA 3
Process Node TSMC 5nm (XCD compute dies) + 6nm (I/O dies)
Package Design Chiplet — 8x XCD + 4x IOD, 3D-stacked
Form Factor OAM (OCP Accelerator Module)
Cooling Passive (data center liquid/air-cooled chassis)
Launch Date December 2023
Core Compute Specifications
Compute Units 304
Stream Processors 19,456
Matrix Cores 1,216
Base Clock ~1,000 MHz
Boost Clock ~2,100 MHz
Infinity Cache 256 MB (shared)
Memory Configuration
GPU Memory 192 GB HBM3
Memory Bus 8,192-bit
Peak Memory Bandwidth 5.3 TB/s
8-GPU Node Pooled Memory 1.5 TB HBM3
Compute Performance (Peak Theoretical)
FP64 ~81.7 TFLOPS
FP32 ~163.4 TFLOPS
FP16 / BF16 1,307.4 TFLOPS (2,614.9 TFLOPS with sparsity)
FP8 2,614.9 TFLOPS (5,229.8 TFLOPS with sparsity)
Connectivity & Interface
Host Interface PCIe Gen 5
GPU-to-GPU Interconnect 4th-Gen AMD Infinity Fabric
Aggregate P2P Bandwidth (8-GPU UBB) Up to 896 GB/s
Power & Thermal
TDP Up to 750W
Recommended PSU 800W+, 80 PLUS Platinum or higher
Software Support
Software Stack AMD ROCm (open-source)
Frameworks PyTorch, TensorFlow, JAX, ONNX Runtime
CUDA Portability HIP conversion tooling for CUDA-to-ROCm porting

Real-World Use Cases

Large Language Model Inference

Serve 70B+ parameter models such as Llama 2/3-class LLMs on a single MI300X instead of splitting them across multiple GPUs, reducing inter-GPU communication overhead and improving throughput for chatbots, copilots, and enterprise assistants.

Generative AI & Fine-Tuning

Fine-tune large language and multimodal models with room for larger batch sizes and longer context windows, thanks to the extra memory headroom beyond the base model footprint.

High-Performance Computing (HPC)

With strong FP64 double-precision throughput, the MI300X supports scientific simulation workloads including computational fluid dynamics, molecular dynamics, and genomics research alongside AI workloads on the same infrastructure.

Multi-GPU Distributed Training

Scale out across 8x MI300X nodes connected via Infinity Fabric for distributed pretraining and large-batch fine-tuning jobs that need both high compute density and pooled memory.

Open-Source AI Development

Teams standardizing on open frameworks — PyTorch, vLLM, Hugging Face — can deploy on ROCm without rewriting pipelines for a proprietary stack, useful for organizations prioritizing multi-vendor flexibility.

Enterprise AI & Data Analytics

Power retrieval-augmented generation (RAG), document intelligence, recommendation engines, and anomaly detection pipelines that need to hold large embedding indexes and models in GPU memory simultaneously.

Voices of Innovation: How We're Shaping AI Together

We're not just delivering AI infrastructure-we're your trusted AI solutions provider, empowering enterprises to lead the AI revolution and build the future with breakthrough generative AI models.

KPMG optimized workflows, automating tasks and boosting efficiency across teams.

H&R Block unlocked organizational knowledge, empowering faster, more accurate client responses.

TomTom AI has introduced an AI assistant for in-car digital cockpits while simplifying its mapmaking with AI.

Run Larger AI Models with AMD MI300X GPUs

Access up to 192GB HBM3 memory per GPU for LLM inference, generative AI, and high-performance computing. Launch cloud instances in minutes with flexible hourly pricing.

Launch GPU
H200 GPUs

AMD Instinct™ MI300X vs NVIDIA H100 SXM: Which GPU Is Better for AI?

The AMD Instinct™ MI300X is designed for large AI models with 192GB HBM3 memory, 5.3 TB/s bandwidth, and higher AI throughput than the NVIDIA H100. It enables larger models to run on fewer GPUs, reducing infrastructure costs for LLM inference and generative AI.

Feature AMD MI300X NVIDIA H100 SXM
GPU Memory 192GB HBM3 80GB HBM3
Memory Bandwidth 5.3 TB/s 3.35 TB/s
FP16/BF16 (Sparsity) 2,614.9 TFLOPS 1,979.8 TFLOPS
FP8 (Sparsity) 5,229.8 TFLOPS 3,957.8 TFLOPS
Software AMD ROCm NVIDIA CUDA

Why Choose MI300X?

● 2.4× more memory for larger AI models

● Higher AI performance for FP16/BF16 and FP8 workloads

● Greater memory bandwidth for faster inference

● Open-source ROCm platform with no vendor lock-in

The MI300X is an excellent choice for LLM inference, generative AI, and memory-intensive HPC workloads, while the H100 remains ideal for CUDA-based AI environments

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Why Choose Cyfuture AI for AMD MI300X GPU Server Rental

Cyfuture AI's AMD MI300X GPU server gives you on-demand access to 192GB of HBM3 memory and 5.3 TB/s of bandwidth per GPU, without the capital cost of owning the hardware. Whether you need a single accelerator for experimentation or a full 8-GPU node for production-scale LLM inference and training, our GPU as a Service model scales with your workload.
Unlike fixed hardware purchases, renting MI300X cloud GPU capacity from Cyfuture AI means you pay for what you use — hourly, monthly, or on reserved terms — with transparent AMD MI300X pricing and no hidden fees. Every instance is backed by enterprise SLAs, 99.9% uptime, rapid deployment, and a support team available 24/7 to help with ROCm setup, framework configuration, and workload optimization.
Choose Cyfuture AI to rent AMD MI300X GPU servers that combine massive memory capacity, an open software ecosystem, and enterprise-grade reliability — built for teams that need to run large models without large hardware bills.

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FAQs:

The power of AI, backed by human support

At Cyfuture AI, we combine advanced technology with genuine care. Our expert team is always ready to guide you through setup, resolve your queries, and ensure your experience with Cyfuture AI remains seamless. Reach out through our live chat or drop us an email at [email protected] - help is only a click away.

Cyfuture AI's AMD MI300X GPU server runs on AMD's CDNA 3 architecture, purpose-built for AI training, LLM inference, and high-performance computing. With 192GB of HBM3 memory and 304 compute units, it's designed to handle memory-intensive models that don't fit comfortably on smaller accelerators.

  • Architecture: AMD CDNA 3
  • GPU Memory: 192GB HBM3
  • Stream Processors: 19,456
  • Memory Bandwidth: 5.3 TB/s
  • Power Consumption: Up to 750W
  • Interface / Form Factor: PCIe Gen 5, OAM
  • Large language model inference and fine-tuning
  • Generative AI and multimodal model training
  • HPC workloads requiring strong FP64 performance
  • Multi-GPU distributed training
  • Enterprise AI applications such as RAG and analytics

The MI300X offers roughly 2.4x the memory capacity of an H100 SXM (192GB vs. 80GB) and higher peak theoretical memory bandwidth, which benefits memory-bound inference of large models. The H100 generally retains an edge in software maturity and measured utilization on CUDA-optimized workloads, so the better fit depends on whether your workload is memory-bound or compute-and-tooling-bound.

Yes. Cyfuture AI lets you rent AMD MI300X GPU capacity for flexible terms — hourly, monthly, or custom reserved plans — with cloud-based provisioning so you can scale up or down without upfront hardware costs.

  • 24/7 technical assistance and proactive monitoring
  • High-availability infrastructure backed by an enterprise SLA
  • Expert guidance on ROCm setup, framework configuration, and deployment optimization

You can provision an MI300X instance directly through Cyfuture AI's cloud portal, or contact our sales team for custom multi-GPU node configurations and current AMD MI300X price and reserved-plan discounts.

  • Largest single-GPU memory capacity in its class, ideal for large model inference
  • Open-source ROCm stack with no single-vendor lock-in
  • Competitive AMD MI300X pricing relative to comparable accelerators
  • Enterprise-grade reliability and expert support from Cyfuture AI

Need More GPU Memory for Your AI Workloads?

Deploy AMD MI300X GPU servers with industry-leading memory capacity, the ROCm software stack, and enterprise-grade infrastructure to power training and inference at scale.

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