AMD MI300X GPU
Access AMD MI300X GPUs across global providers. Compare pricing, locations, configurations, and deployment options — without vendor lock-in.
What is the AMD MI300X GPU?
The AMD MI300X is a high-memory AI accelerator built on AMD's CDNA 3 architecture, designed for large-scale AI workloads that are constrained by memory capacity and bandwidth.
Unlike many previous-generation accelerators, MI300X places a strong emphasis on memory density, offering 192 GB of HBM3 on a single GPU.
MI300X GPUs are commonly deployed as reserved capacity by AI startups, research teams, and enterprises seeking predictable performance for sustained inference or data-intensive model workloads.
AMD MI300X SPECIFICATIONS
WHAT IS MI300X USED FOR?
Large language model inference
MI300X is widely used for high-throughput LLM inference, where large model weights and long context windows benefit from high on-GPU memory capacity and bandwidth.
Memory-bound training and fine-tuning
Teams use MI300X for training and fine-tuning workloads where model size or dataset scale exceeds the practical limits of lower-memory GPUs, reducing the need for aggressive model sharding.
Long-context and retrieval-augmented workloads
MI300X is well suited for workloads involving long sequences, retrieval-augmented generation, and large embedding stores, where memory footprint is a primary constraint.
Multi-node distributed workloads
MI300X systems are deployed in multi-node environments, using high-speed on-node interconnects and InfiniBand-based networking across nodes, depending on provider infrastructure and system design.
H100 Pricing Is Not Fixed - It's A Market
H100 pricing varies significantly depending on region, provider type, configuration, networking, and demand cycles. Public cloud rates often differ materially from neocloud and bare-metal offerings.
- Live H100 availability
- Regional price differences
- Configuration comparisons
- Flexible deployment options
Instead of negotiating blindly with a single vendor, teams can evaluate the true market for H100 capacity before committing.
HOW YOU CAN DEPLOY
- Cloud instances (on-demand or contract-based)
- Neocloud providers with optimized AI infrastructure
- Bare-metal servers for maximum control
- Single-node or multi-node clusters
- Short-term burst capacity or longer-term allocations
"Compute Exchange acts as a broker and marketplace layer, helping buyers match workload needs to the right supply — without forcing architectural changes."
Why Buy H100 Through Compute Exchange
Verified Suppliers
Access to verified H100 suppliers globally
Transparent Comparison
Clear view across providers and regions
Faster Sourcing
Faster sourcing than bilateral negotiations
Complex Requirements
Support for networking, scaling, and compliance
Find The Right H100 Capacity For Your Workload
The NVIDIA GB200 Grace Blackwell Superchip connects two NVIDIA B200 Tensor Core GPUs to the NVIDIA Grace CPU over a high-speed NVLink-C2C interconnect.