A100 SXM4 80GB on TensorDock
Visit TensorDockTensorDock delivers the NVIDIA A100 SXM4 80GB, an enterprise-grade Ampere GPU with 80GB HBM2e VRAM, optimized for AI training, large language model fine-tuning, data analytics, and HPC workloads. This offering stands out due to TensorDock's marketplace model, which provides extremely low spot prices—often 70-80% below on-demand rates—stabilized post-acquisition by Voltage Park for reliable inventory. Ideal for cost-sensitive ML engineers and data scientists handling memory-intensive tasks like training models with billions of parameters. Key value propositions include per-second billing for precise cost control, spot instances for bursty workloads, and seamless access to high-performance compute without long-term commitments. The A100's 7th-gen Tensor Cores deliver up to 312 TFLOPS in TF32, enabling efficient scaling across multi-GPU setups. This combination democratizes access to top-tier hardware, balancing performance and affordability for production and experimentation.
Why NVIDIA A100 SXM4 80GB on TensorDock?
Choose TensorDock for the A100 SXM4 80GB to leverage the lowest spot prices in the GPU marketplace, often under $1/hour, thanks to competitive bidding and Voltage Park's inventory stabilization. The per-second billing model perfectly suits the A100's high-utilization profiles, avoiding overpayment on idle time. Marketplace dynamics ensure high availability of these scarce 80GB variants, ideal for VRAM-hungry workloads like LLMs. Unlike fixed-price providers, TensorDock's flexibility complements the GPU's NVLink multi-GPU capabilities for distributed training. Cost savings enable longer runs or larger batches without sacrificing enterprise reliability, making it superior for budget-conscious teams prioritizing value over premium support.
Live Pricing
Real-time NVIDIA A100 SXM4 80GB offers from TensorDock
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 0 vCPU 0GB RAM | Mischii, Dolj | $0.85/GPU/hr | Sold Out | ||
TensorDock | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 0 vCPU 0GB RAM | Prague | $1.20/GPU/hr | Sold Out |
Performance Notes
The A100 SXM4 80GB on TensorDock delivers benchmark-equivalent performance: 19.5 TFLOPS FP64, 312 TFLOPS TF32 Tensor Core, and 2 TB/s memory bandwidth. Multi-GPU scaling via NVLink (up to 8 GPUs) is supported, though exact topology varies by host. Network bandwidth typically 100-200 Gbps (InfiniBand/RoCE unconfirmed—verify docs). Fast NVMe storage options enable quick dataset loading. Spot instances risk interruptions (monitor via API), so implement checkpointing. No provider-specific benchmarks available; expect near-native speeds for PyTorch/TensorFlow, but test interconnects for NCCL collectives. Ideal for single-node or small clusters.
A GPU marketplace offering extremely low spot prices, stabilized by acquisition by Voltage Park.
Best For
Unique Features
- Marketplace model
- Stabilized inventory post-acquisition
VRAM
80GB
Architecture
Ampere
Tier
enterprise
Platform Features
Getting Started
TensorDock's user-friendly dashboard simplifies launching A100 SXM4 80GB instances. Sign up, fund your account, select spot/on-demand pricing, and deploy pre-configured ML images with NVIDIA drivers, CUDA 12.x, and frameworks like PyTorch. Connect via SSH or Jupyter for immediate productivity.
Steps
- 1Create a TensorDock account and add payment/credits via dashboard.
- 2Navigate to Marketplace, filter for A100 SXM4 80GB, select spot instance.
- 3Configure vCPU/RAM/storage, choose image (e.g., Ubuntu + CUDA), and launch.
- 4Access instance via SSH (keys auto-generated) or web console.
- 5Install ML libs (pip install torch) and start workloads.
Pro Tips
- Opt for spot instances for max savings, but enable auto-resume and frequent checkpoints to handle preemptions.
- Use multi-GPU configs with NCCL for training; test NVLink bandwidth first with simple benchmarks.
- Leverage per-second billing by scripting short-lived jobs; monitor costs via API for optimization.
Frequently Asked Questions
What is TensorDock's billing model for NVIDIA A100 SXM4 80GB?▾
TensorDock 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 TensorDock offer spot instances for NVIDIA A100 SXM4 80GB?▾
Yes, TensorDock 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.
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