A100 SXM4 80GB on FluidStack
Visit FluidStackFluidStack's NVIDIA A100 SXM4 80GB offering combines the enterprise-grade Ampere GPU with a supercloud aggregator model, delivering 80GB HBM2e VRAM for memory-intensive AI workloads like large-scale model training, fine-tuning LLMs, and HPC simulations. This setup stands out for its ability to provision massive clusters instantly from pooled global resources across Tier 1-4 data centers, bypassing traditional lead times. Ideal for ML engineers and data scientists requiring burst capacity for distributed training without infrastructure ownership. Key value propositions include per-minute billing for precise cost control, spot instances for up to 70% savings on interruptible workloads, and a unified API for seamless orchestration. FluidStack's aggregation of spare capacity ensures high availability worldwide, making it perfect for global teams optimizing for scale, speed, and economics in production AI pipelines. While performance varies by data center, the A100's 19.5 TFLOPS FP64 and multi-instance GPU (MIG) support enable efficient resource partitioning.
Why NVIDIA A100 SXM4 80GB on FluidStack?
Choose FluidStack for NVIDIA A100 SXM4 80GB when needing rapid access to hundreds or thousands of these GPUs for large-scale training, as their supercloud pools underutilized capacity from diverse data centers worldwide. This aggregation provides unmatched immediacy and elasticity—scale from 1 to 10,000+ GPUs in minutes via a single interface. Per-minute billing and spot instances complement the A100's high VRAM and compute density, slashing costs for variable workloads versus fixed reservations elsewhere. FluidStack's global footprint minimizes latency for distributed teams, while NVLink-compatible hosts enable tight multi-GPU scaling. Unique edge: cost-effective entry to 80GB A100s without colocation commitments, ideal for bursty AI projects where traditional providers falter on availability.
Live Pricing
Real-time NVIDIA A100 SXM4 80GB offers from FluidStack
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 FluidStack | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 0 vCPU 0GB RAM | 🌍Global | $1.30/GPU/hr $10.40/hr total (8×) |
Performance Notes
On FluidStack, expect NVIDIA A100 SXM4 80GB to deliver flagship Ampere performance: up to 312 TFLOPS FP16 with Tensor Cores, excelling in transformer training and inference. Networking varies by data center (typically 100-400 Gbps InfiniBand or Ethernet), supporting efficient multi-node scaling via NCCL. Multi-GPU configs leverage NVLink for low-latency inter-GPU communication, with hosts offering 8x A100 pods. Storage includes NVMe SSDs (up to 30TB local) for fast checkpoints. MIG enables up to 7 instances per GPU. Actual throughput depends on location and spot vs. on-demand; benchmarks show near-native DGX speeds in top-tier DCs, but Tier 4 may have higher variability—test with small jobs first.
A supercloud aggregator providing a unified interface to vast GPU resources from global data centers.
Best For
Unique Features
- Supercloud architecture pooling global resources
- Aggregation of spare capacity from Tier 1-4 data centers
VRAM
80GB
Architecture
Ampere
Tier
enterprise
Platform Features
Getting Started
Getting started with FluidStack's A100 SXM4 80GB is straightforward via their web console or API. Create an account, fund via credit card or wire, and launch instances from the GPU marketplace. Pre-built images with CUDA 12.x, PyTorch, and TensorFlow accelerate ML workflows. Scale clusters dynamically with Kubernetes integration.
Steps
- 1Sign up at fluidstack.io and complete KYC verification (under 5 minutes).
- 2Add payment method and minimum deposit ($100+ for GPUs).
- 3Navigate to GPU Marketplace, filter for A100 SXM4 80GB, select region/config.
- 4Choose on-demand/spot, image (e.g., Ubuntu+Cuda), and launch instance.
- 5SSH/RDP in, install dependencies, and start training via Jupyter or CLI.
Pro Tips
- Opt for spot instances on non-critical jobs to save 50-70%; set auto-failover to on-demand.
- Use FluidStack's Orchestrator for auto-scaling Kubernetes clusters across regions.
- Benchmark network with NCCL tests early, prioritizing Tier 1 DCs for multi-node training.
Frequently Asked Questions
What is FluidStack's billing model for NVIDIA A100 SXM4 80GB?▾
FluidStack bills per-minute for GPU instances including NVIDIA A100 SXM4 80GB. Check their pricing page for the most current billing details.
Does FluidStack offer spot instances for NVIDIA A100 SXM4 80GB?▾
Yes, FluidStack 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.
Does FluidStack offer reserved instances for NVIDIA A100 SXM4 80GB?▾
Yes, FluidStack 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 FluidStack for current reserved pricing and commitment terms.
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