Rent A100 80GB
Compare live on-demand and spot rental prices across 97+ cloud providers. Workhorse of the AI era. Widely available, mature software support, excellent price/performance.
Choosing the right billing model for A100 80GB
Provision and terminate at any time. Ideal for development, short experiments, and workloads with unpredictable duration.
Instances can be reclaimed when demand spikes. Best for fault-tolerant batch jobs, training with checkpointing, and preprocessing.
Lock in a rate for 1–3 months. Right for sustained production inference or long training runs where cost predictability matters.
Best use cases
- ML training
- Large model inference
- HPC workloads
A100 80GB — Specs & Benchmarks
Performance bars, compute tiers (FP32/FP16/BF16/FP8/INT8), memory specs, LLM model size guidance, and related GPU comparisons.
A100 80GB Rental Guide
The A100 80GB is the most cost-effective choice for training models in the 7B–30B parameter range and for inference serving of models up to 70B at INT8. Its 80GB HBM2e fits Llama 3.1 70B at INT8 (70GB) on a single card, making it the most affordable single-GPU option for 70B inference. On-demand rates range from $1.50–$3.50/hr across providers — significantly cheaper than H100 for workloads that don't require FP8 or higher memory bandwidth.
Spot instances for A100 80GB are widely available at 40–60% below on-demand rates. The A100 is the most common spot GPU at scale, with high availability across Lambda Labs, CoreWeave, Vast.ai, and RunPod. For batch training jobs with checkpointing, A100 spot is often the best cost-per-FLOP option available. On-demand is appropriate for production inference serving where uptime matters.
When comparing A100 providers, distinguish between SXM4 (2,039 GB/s HBM2e, 600 GB/s NVLink) and PCIe (1,935 GB/s HBM2e, no NVLink) variants. For multi-GPU tensor parallelism, SXM4 is meaningfully faster. For single-card inference, the PCIe variant is often 15–25% cheaper with minimal throughput difference. The A100 is also available in a 40GB configuration at lower cost — suitable for models up to ~30B parameters at FP16.
Frequently Asked Questions
How much does it cost to rent a A100 80GB?
A100 80GB on-demand rental prices vary by provider and region. On-demand rates typically range based on availability and provider margins — use the comparison table above to see current live rates across all providers. Spot instances are generally 40–70% cheaper than on-demand but can be interrupted. Monthly cost estimates (hourly rate × 730 hours) are shown in the table for sustained workloads.
Which cloud provider has the cheapest A100 80GB?
The cheapest A100 80GB provider changes as providers update their pricing. The comparison table above shows live rates sorted by price, so the cheapest option is always at the top. Factors beyond headline price include region (latency to your users), availability (high/medium/low), and billing granularity (per-second vs per-hour minimums).
What can I run on a A100 80GB?
With 80GB of HBM2e, the A100 80GB can run LLM models up to approximately 40B parameters at FP16, 80B at INT8, or 160B at INT4/GGUF quantization. Common workloads include: ML training, Large model inference, HPC workloads. Workhorse of the AI era. Widely available, mature software support, excellent price/performance.
Should I use on-demand or spot pricing for A100 80GB?
Spot instances save 40–70% vs on-demand but can be interrupted when the provider needs capacity back. Use spot for: batch inference jobs, training runs with checkpointing, preprocessing pipelines, and any workload that can tolerate interruption and restart. Use on-demand for: production inference serving, interactive workloads, and jobs that cannot be interrupted. Most providers bill per second, so short on-demand jobs are not penalized by hourly minimums.
How does the A100 80GB compare to the H100 for cloud rental?
The H100 80GB delivers 1,979 TFLOPS FP16 with 3,350 GB/s HBM3 bandwidth, compared to the A100 80GB's 312 TFLOPS FP16 and 2000 GB/s bandwidth. The H100 is significantly more expensive — typically $2.50–$5.00/hr vs lower rates for the A100 80GB. For workloads that fit within 80GB and don't require FP8 precision, the A100 80GB often delivers better cost-per-token than the H100.
What is the memory bandwidth of the A100 80GB and why does it matter?
The A100 80GB has 2000 GB/s of memory bandwidth. For LLM inference, memory bandwidth is often more important than raw TFLOPS — each autoregressive token generation reads the full model weight matrix from VRAM, so bandwidth directly determines tokens-per-second throughput. Higher bandwidth means faster inference for the same model at the same batch size. For batch inference (processing many requests simultaneously), compute throughput becomes more important.
Can I use the A100 80GB for Stable Diffusion or image generation?
Yes — the A100 80GB is capable for Stable Diffusion and image generation workloads. Image generation is primarily FP32 and FP16 compute-bound, and the A100 80GB's 19.5 TFLOPS FP32 throughput determines images-per-second. The 80GB VRAM fits SDXL (requires ~6GB) and most ControlNet pipelines. For high-throughput image generation at scale, compare cost-per-image across providers using the GPU cost calculator.