MI300X on Crusoe
Visit CrusoeCrusoe, a climate-aligned computing provider, offers the AMD Instinct MI300X GPU with 192GB HBM3 VRAM on its CDNA 3 architecture, tailored for enterprise HPC and AI workloads. This combination stands out by pairing the MI300X's exceptional memory bandwidth (5.3 TB/s) and compute density—ideal for large-scale training of LLMs, inference, and memory-bound simulations—with Crusoe's sustainable infrastructure powered by stranded energy sources. Target audience includes organizations with strict ESG mandates, such as research institutions and enterprises tracking carbon footprints in batch training pipelines. Key value propositions: vertically integrated energy-to-cloud model for reliable, low-latency scaling; per-hour billing with spot instances for cost efficiency (up to 70-90% savings); and alignment of high-power MI300X (750W TDP) with eco-friendly power sourcing, reducing Scope 2 emissions. ML engineers gain access to cutting-edge AMD hardware in a platform prioritizing environmental responsibility without sacrificing performance.
Why AMD Instinct MI300X on Crusoe?
Choose Crusoe for AMD Instinct MI300X to leverage sustainable power from stranded methane and flared gas sources, perfectly suiting the GPU's 750W TDP and high energy demands for prolonged AI training runs. Crusoe's vertical integration—from energy capture to cloud delivery—ensures low-cost, reliable infrastructure with minimal downtime, complementing MI300X's strengths in memory-intensive workloads like MoE models or FP8 training. Per-hour billing and spot instances optimize costs for interruptible batch jobs, while ESG reporting tools provide verifiable carbon metrics. Unlike traditional hyperscalers, this combo offers unmatched environmental alignment without networking or scaling compromises, ideal for green-conscious teams scaling to 8+ GPUs.
Live Pricing
Real-time AMD Instinct MI300X offers from Crusoe
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
![]() Crusoe | AMD Instinct MI300X 192GB VRAM | 192GB | 0 vCPU 0GB RAM | United States | $0.95/GPU/hr | |||
![]() Crusoe | AMD Instinct MI300X 192GB VRAM | 192GB | 0 vCPU 0GB RAM | United States | $3.45/GPU/hr |


Performance Notes
On Crusoe, expect MI300X to deliver near-native performance for ROCm-optimized workloads, with 192GB VRAM enabling models up to 1.8T params in FP16. Multi-GPU scaling via Infinity Fabric and ROCm supports efficient 8-GPU clusters for training throughput comparable to H100 pods (e.g., 2-3x memory advantage). Network bandwidth likely 400-800 Gb/s RoCE/InfiniBand (provider-optimized for HPC), paired with NVMe storage options up to 100 GB/s. DGX-like configs enable strong weak/strong scaling; however, exact benchmarks are emerging—real-world MLPerf results pending public disclosure. Power efficiency shines in sustained batch runs, but verify ROCm 6.0+ compatibility for custom kernels.
A climate-aligned computing provider powering high-performance computing using stranded energy sources to mitigate environmental impact.
Best For
Unique Features
- Vertically integrated energy-to-cloud model
- Use of stranded energy sources
VRAM
192GB
Architecture
CDNA 3
Tier
enterprise
Platform Features
Getting Started
Getting started with AMD Instinct MI300X on Crusoe is straightforward via their web console or API. Sign up for an account, select sustainable clusters, and launch instances optimized for ROCm. Access Jupyter, SSH, or Slurm for workloads, with spot options for cost savings.
Steps
- 1Create a Crusoe account and complete KYC verification (1-2 business days).
- 2Navigate to console, choose a low-carbon region/cluster with MI300X availability.
- 3Select instance type (e.g., 8x MI300X), configure CPU/RAM/storage, and opt for spot if batch.
- 4Deploy with pre-built ROCm images (Ubuntu 22.04 + ROCm 6.1), add public IP or VPC.
- 5Connect via SSH/JupyterHub; run 'rocm-smi' to verify GPUs and start workloads.
Pro Tips
- Prioritize spot instances for batch training to cut costs by 70-90%; use Slurm for fault-tolerant queuing.
- Leverage MI300X's HBM3 for memory-bound tasks like Llama 405B fine-tuning; enable HIP for portability from CUDA.
- Monitor carbon dashboard for ESG reporting; test scaling with ROCm's MI300X-optimized libraries first.
Frequently Asked Questions
What is Crusoe's billing model for AMD Instinct MI300X?▾
Crusoe bills per-hour for GPU instances including AMD Instinct MI300X. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Crusoe offer spot instances for AMD Instinct MI300X?▾
Yes, Crusoe offers spot/preemptible instances for AMD Instinct MI300X, which can reduce costs by 50-80% compared to on-demand pricing. Spot instances are ideal for fault-tolerant workloads like batch inference, hyperparameter tuning, and training jobs with checkpointing. Note that spot instances can be interrupted when demand is high, so ensure your workflow can handle preemption gracefully.
How can I access AMD Instinct MI300X instances on Crusoe?▾
Crusoe provides access to AMD Instinct MI300X instances via SSH, programmatic API, Docker containers. SSH access gives you full control over the instance for custom configurations and production deployments. API access enables automation and integration with your existing ML pipelines and CI/CD workflows.
What compliance certifications does Crusoe have for AMD Instinct MI300X workloads?▾
Crusoe maintains SOC 2, GDPR certifications, making it suitable for regulated workloads. SOC 2 certification demonstrates strong security controls for handling sensitive data. Contact Crusoe directly for detailed compliance documentation and BAA agreements if needed.
Can I use AMD Instinct MI300X with Kubernetes on Crusoe?▾
Yes, Crusoe supports Kubernetes for orchestrating AMD Instinct MI300X workloads. This enables you to deploy scalable ML pipelines, manage distributed training jobs across multiple GPUs, and integrate with MLOps tools like Kubeflow, Argo Workflows, and KServe. Kubernetes support is essential for teams building production-grade ML infrastructure.
What are the specifications of the AMD Instinct MI300X?▾
The AMD Instinct MI300X features 192GB of high-bandwidth memory, built on NVIDIA's CDNA 3 architecture. As an enterprise-tier GPU, it's designed for large-scale AI training, inference at scale, and demanding HPC workloads. The substantial VRAM capacity supports large language models, complex neural networks, and multi-model deployments.
What workloads is AMD Instinct MI300X on Crusoe best suited for?▾
The AMD Instinct MI300X on Crusoe is well-suited for large-scale AI/ML training, LLM fine-tuning, batch inference at scale, and high-performance computing workloads. Crusoe specifically excels at: Organizations with strict ESG mandates; Batch training workloads where carbon footprint is a key metric. Consider your model size, training data volume, and latency requirements when evaluating this combination for your specific use case.
Does Crusoe offer reserved instances for AMD Instinct MI300X?▾
Yes, Crusoe offers reserved instance pricing for AMD Instinct MI300X, which can provide significant discounts (typically 20-40% off on-demand rates) for committed usage periods. Reserved instances are ideal for predictable, long-running workloads like production inference services, ongoing training pipelines, or development environments that run continuously. Contact Crusoe for current reserved pricing and commitment terms.
What unique features does Crusoe offer for AMD Instinct MI300X?▾
Crusoe differentiates itself with: Vertically integrated energy-to-cloud model; Use of stranded energy sources. These features may provide advantages depending on your specific workflow requirements and technical needs. Evaluate how these capabilities align with your ML infrastructure goals when making your decision.
How do I get started with AMD Instinct MI300X on Crusoe?▾
To get started with AMD Instinct MI300X on Crusoe, visit https://crusoe.ai?utm_source=gpuperhour&utm_medium=referral to create an account. Most providers offer a straightforward signup process, and some provide initial credits for new users. Once registered, you can typically launch a AMD Instinct MI300X instance within minutes through their dashboard or API. We recommend starting with a small experiment to familiarize yourself with the platform before scaling up to larger workloads.
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