A100 SXM4 80GB on CoreWeave
Visit CoreWeaveCoreWeave's NVIDIA A100 SXM4 80GB offering delivers enterprise-grade performance for massive-scale AI training and VFX rendering. This Ampere architecture GPU boasts 80GB HBM2e VRAM, enabling handling of large language models (LLMs) and complex simulations that exceed consumer-grade hardware limits. CoreWeave's Kubernetes-native platform optimizes orchestration, allowing seamless scaling across InfiniBand-connected clusters up to thousands of GPUs. Ideal for sophisticated ML engineering teams and VFX studios, it supports per-second billing and spot instances for cost efficiency without sacrificing reliability. Key value propositions include low-latency networking for distributed training, MIG partitioning for multi-tenant workloads, and direct access to cutting-edge infrastructure purpose-built for AI/HPC. This combination empowers efficient fine-tuning of models like GPT-scale transformers, inference at production volumes, and burst rendering, reducing time-to-results for high-stakes projects.
Why NVIDIA A100 SXM4 80GB on CoreWeave?
Choose CoreWeave for NVIDIA A100 SXM4 80GB due to its Kubernetes-native architecture, which simplifies deploying and scaling multi-GPU workloads via familiar kubectl commands or console. Massive InfiniBand clusters (up to 400Gb/s) complement the A100's NVLink capabilities, minimizing communication overhead in distributed training. Per-second billing and spot instances offer up to 70% savings versus on-demand rivals, ideal for variable workloads. Unlike general clouds, CoreWeave's AI-focused optimizations—like pre-tuned NCCL and fast NVMe storage—maximize the 80GB VRAM for memory-intensive tasks such as LLM pretraining. This setup excels for teams needing hyperscale without custom infra management.
Live Pricing
Real-time NVIDIA A100 SXM4 80GB offers from CoreWeave
No offers currently available for NVIDIA A100 SXM4 80GB on CoreWeave.
View NVIDIA A100 SXM4 80GB from all providersPerformance Notes
On CoreWeave, expect A100 SXM4 80GB to deliver peak FP32 at 19.5 TFLOPS and FP16 at 312 TFLOPS with Tensor Cores, enhanced by NVLink 3.0 for 600 GB/s GPU-to-GPU bandwidth. InfiniBand RDMA enables efficient multi-node scaling, with benchmarks showing near-linear speedup up to 256+ GPUs for PyTorch DDP jobs. NVMe storage options provide 10-100 GB/s throughput, suiting large dataset I/O. MIG supports up to 7 instances per GPU for isolation. Actual performance varies by workload and cluster config; CoreWeave publishes select benchmarks, but user testing recommended for specifics like your model's all-reduce efficiency.
A premier specialized GPU cloud designed for massive-scale AI training and VFX rendering with Kubernetes-native architecture.
Best For
Unique Features
- Kubernetes-native architecture
- Access to massive-scale InfiniBand clusters
VRAM
80GB
Architecture
Ampere
Tier
enterprise
Platform Features
Getting Started
Getting started with CoreWeave's A100 SXM4 80GB is streamlined via their web console or Kubernetes CLI. Sign up for instant access to on-demand or spot instances, deploy pods with NVIDIA operators pre-installed, and scale clusters effortlessly. Focus on your ML pipeline while Kubernetes handles orchestration.
Steps
- 1Create a CoreWeave account and add payment method via the console.
- 2Launch Mission Control to create a Kubernetes cluster with A100 SXM4 80GB nodes.
- 3Apply a pod YAML specifying nvidia.com/gpu: '1' and your Docker image (e.g., NGC PyTorch).
- 4Connect via kubectl port-forward or SSH for Jupyter/CLI access.
- 5Monitor scaling and costs in real-time through the dashboard.
Pro Tips
- Leverage spot instances for non-urgent training to cut costs by 50-70%; set disruption budgets to minimize interruptions.
- Use MIG partitioning for concurrent inference/fine-tuning on single GPUs, boosting utilization in shared clusters.
- Pre-pull large containers and datasets to NVMe volumes to accelerate startup times in InfiniBand environments.
Frequently Asked Questions
What is CoreWeave's billing model for NVIDIA A100 SXM4 80GB?▾
CoreWeave bills per-second for GPU instances including NVIDIA A100 SXM4 80GB. Per-second billing ensures you only pay for exactly the compute time you use, which is particularly cost-effective for short experiments, iterative development, and workloads with variable duration.
Does CoreWeave offer spot instances for NVIDIA A100 SXM4 80GB?▾
Yes, CoreWeave offers spot/preemptible instances for NVIDIA A100 SXM4 80GB, 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 NVIDIA A100 SXM4 80GB instances on CoreWeave?▾
CoreWeave provides access to NVIDIA A100 SXM4 80GB instances via SSH, built-in Jupyter notebooks, web-based terminal, programmatic API, Docker containers. The built-in Jupyter notebook support makes it easy to start experimenting immediately without additional setup. 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 CoreWeave have for NVIDIA A100 SXM4 80GB workloads?▾
CoreWeave maintains SOC 2, HIPAA, GDPR, ISO 27001 certifications, making it suitable for regulated workloads. HIPAA compliance is particularly important for healthcare and medical AI applications. SOC 2 certification demonstrates strong security controls for handling sensitive data. Contact CoreWeave directly for detailed compliance documentation and BAA agreements if needed.
Can I use NVIDIA A100 SXM4 80GB with Kubernetes on CoreWeave?▾
Yes, CoreWeave supports Kubernetes for orchestrating NVIDIA A100 SXM4 80GB 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 NVIDIA A100 SXM4 80GB?▾
The NVIDIA A100 SXM4 80GB features 80GB of high-bandwidth memory, built on NVIDIA's Ampere 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 NVIDIA A100 SXM4 80GB on CoreWeave best suited for?▾
The NVIDIA A100 SXM4 80GB on CoreWeave is well-suited for large-scale AI/ML training, LLM fine-tuning, batch inference at scale, and high-performance computing workloads. CoreWeave specifically excels at: Sophisticated engineering teams training LLMs at scale; VFX studios requiring burst rendering capacity. Consider your model size, training data volume, and latency requirements when evaluating this combination for your specific use case.
Does CoreWeave offer reserved instances for NVIDIA A100 SXM4 80GB?▾
Yes, CoreWeave offers reserved instance pricing for NVIDIA A100 SXM4 80GB, 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 CoreWeave for current reserved pricing and commitment terms.
What unique features does CoreWeave offer for NVIDIA A100 SXM4 80GB?▾
CoreWeave differentiates itself with: Kubernetes-native architecture; Access to massive-scale InfiniBand clusters. 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 NVIDIA A100 SXM4 80GB on CoreWeave?▾
To get started with NVIDIA A100 SXM4 80GB on CoreWeave, visit https://www.coreweave.com?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 NVIDIA A100 SXM4 80GB 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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