A100 SXM 80GB from $0.19 per GPU-hour
Still the workhorse of fine-tuning. 80 GB of HBM2e and NVLink make it comfortable for models an RTX card cannot hold, at a fraction of the price of Hopper. No FP8, so plan on FP16 or integer quantisation.
Billed per started minute. 640 GB of GPU memory on a 8× node. Persistent storage $0.08 per GB-month. No egress fees.
- GPU memory
- 80GBHBM2e · MIG capable
- Bandwidth
- 2,039GB/sSets token throughput on inference
- Node sizes
- 1× · 2× · 4× · 8×Same price per GPU at every size
- Reclaim rate
- <5%Spot instances reclaimed over 30 days
What you get with each A100 node.
| Node | GPU memory | vCPU | RAM | Local NVMe | Spot | On-demand | Action |
|---|---|---|---|---|---|---|---|
| 1× A100 | 80 GB | 16 | 128 GB | 1 TB | $0.19/h | $0.29/h | Configure |
| 2× A100 | 160 GB | 32 | 256 GB | 2 TB | $0.38/h | $0.58/h | Configure |
| 4× A100 | 320 GB | 64 | 512 GB | 4 TB | $0.76/h | $1.16/h | Configure |
| 8× A100 | 640 GB | 128 | 1,024 GB | 8 TB | $1.52/h | $2.32/h | Configure |
GPU-to-GPU link: NVLink 3, 600 GB/s; PCIe Gen4 64 GB/s. Local NVMe is scratch space wiped when the instance ends; keep anything you need on a persistent disk.
96 A100 GPUs free right now.
Straight from the capacity pool the console books against. Prices are identical in every region — pick the one closest to your data.
A region with zero free GPUs still accepts reserved capacity requests — we hold hardware for a term rather than sell what is already taken.
What fits in 80 GB — and what it costs per hour.
Weights need about 2 GB per billion parameters at FP16 / BF16, 0.5 GB per billion parameters at INT4. We keep 20% of the memory free for activations, the KV cache and the CUDA context, then take the smallest node that still fits.
| Open model | Parameters | FP16 / BF16node · spot price | INT4node · spot price |
|---|---|---|---|
| Mistral 7BAssistants, RAG, classification | 7.2B | 1× $0.19/h | 1× $0.19/h |
| Llama 3.1 8BAssistants, agents, fine-tuning | 8B | 1× $0.19/h | 1× $0.19/h |
| Gemma 2 27BHigher-quality assistants | 27B | 1× $0.19/h | 1× $0.19/h |
| Qwen2.5 32BCode and reasoning | 32B | 1× $0.19/h | 1× $0.19/h |
| Mixtral 8x7BMixture of experts, high throughput | 46.7B | 2× $0.38/h | 1× $0.19/h |
| Llama 3.3 70BThe common production baseline | 70B | 4× $0.76/h | 1× $0.19/h |
| Qwen2.5 72BMultilingual, long context | 72B | 4× $0.76/h | 1× $0.19/h |
| Mixtral 8x22BMixture of experts, large capacity | 141B | 8× $1.52/h | 2× $0.38/h |
| Llama 3.1 405BLargest widely used open model | 405B | over 8× | 4× $0.76/h |
Real usage depends on context length, batch size and the serving engine: a long context can add tens of gigabytes of KV cache. Treat the table as the floor, not the ceiling — and if a job is close to the limit, take the next node size or quantise one step further.
What a dollar buys on an A100.
Ranked 8 of 21 data-center models in this catalogue on cost per gigabyte of GPU memory.
GPU memory you get for $1.00 of spot time, per hour.
Bandwidth decides token throughput far more often than raw FLOPS.
Spot price divided by published FP16 tensor throughput.
One GPU on spot, billed per minute, storage excluded.
Against the rest of the market
70 providers · September 2026- Median on-demand elsewhere
- $1.60Our on-demand is 82% below it
- Cheapest on-demand seen
- $0.40Our on-demand $0.29 is 28% below it
- Cheapest spot seen
- $0.29Our spot $0.19 is 34% below it
- 24 hours on one GPU
- $4.56 on spot$6.96 on-demand · $9.60 at the cheapest rate found elsewhere
Index built from published prices for the same GPU across 137 providers (public price index (getdeploying.com)), September 2026. How the guarantee is enforced.
What people run on an A100 SXM 80GB.
Training and full fine-tuning
Enough memory for optimiser states and activations on models a smaller card can only run in inference.
Serving large models
A 70B model at FP8 across two GPUs, with room for a long context window.
Multi-GPU jobs over NVLink
GPU-to-GPU traffic stays off the PCIe bus, which is what makes tensor and pipeline parallelism worth it.
Partitioned serving (MIG)
The GPU can be split into isolated instances, each with its own memory and compute slice.
NVIDIA A100 SXM 80GB, as published by NVIDIA.
Taken from the vendor datasheet. Where a figure is not published, the row is absent rather than estimated.
- Vendor
- NVIDIA
- Architecture
- Ampere (2020)
- Segment
- Datacenter
- Memory
- 80 GB HBM2e
- Memory bandwidth
- 2,039 GB/s
- FP16 / BF16 tensor
- 312 TFLOPS
- FP32
- 20 TFLOPS
- CUDA cores
- 6,912
- Board power
- 400 W
- Form factor
- SXM4
- Interconnect
- NVLink 3, 600 GB/s; PCIe Gen4 64 GB/s
- Multi-instance (MIG)
- Supported by the GPU
- 8-bit float (FP8)
- Not supported — use FP16 or integer quantisation
Source: www.nvidia.com · images.nvidia.com · verified against the vendor document
Software that runs on it
8 templatesPre-built environments, pulled on the node before you land on it. Or bring any OCI image from a public or private registry.
On the spot tier
<5% reclaimed · 30 d- 2 minutes of notice on the metadata endpoint, a webhook and the console
- The instance is stopped, not deleted — disk and IP stay attached
- Auto-relaunch on the next free A100, or switch the same disk to on-demand
- You save $2.40 a day per GPU against on-demand
If the A100 is not the right fit.
Same memory or more, 53% cheaper on spot
H100 NVL 94 GB HBM3 · Hopper $0.49/h spotNext step up in memory: 94 GB instead of 80 GB
A100 40GB 40 GB HBM2 · Ampere $0.09/h spotSame Ampere generation
A10 24 GB GDDR6 · Ampere $0.09/h spotSame Ampere generation
Or put two of them side by side: A100 vs A100 PCIe · A100 vs H100 NVL · A100 vs A100 40GB
A100 SXM 80GB — the questions that come up
How much does an A100 SXM 80GB cost per hour?
Spot is $0.19 per GPU-hour and on-demand is $0.29, both billed per minute — every started minute costs the hourly price divided by 60, so $0.0032 on spot. Reserved capacity is $0.19 per GPU-hour on a monthly commitment. Storage and egress are not included in that rate: persistent disks are $0.08 per GB-month and there are no egress fees.
How many GPUs can I put in one instance?
Node sizes are 1×, 2×, 4×, 8× — up to 8 A100 SXM 80GB GPUs in a single virtual machine, with CPU, RAM and local NVMe scaled with the GPU count. The price per GPU is identical at every node size.
Can it run a 70B model?
Yes. At FP16, a 70B model needs about 140 GB for the weights, so it fits on 4× A100 SXM 80GB ($0.76 per hour on spot) with roughly 20% of the memory left for activations and the KV cache.
Which regions have it?
Available now in US East (Virginia), US West (Oregon), EU Central (Frankfurt). Prices are identical in every region; pick the one closest to your data.
How often is a spot A100 reclaimed?
Over the trailing 30 days, <5% of spot instances on this model were reclaimed. You get a 2-minute notice on the metadata endpoint, through a webhook and in the console; the instance is then stopped, never deleted, and the persistent disk stays attached.
Anything else about this model? Ask an engineer — the same people run the nodes.
An A100 SXM 80GB for $0.19 an hour, running in under 60 seconds.
Pay as you go — no contracts, no minimum commitment. Add credit, launch, stop whenever you want.
Billed per minute from the moment the instance is reachable. Minimum credit $40, no subscription. 96 A100 GPUs available right now.