A100 80GB vs RTX 4090: Which GPU Should You Choose?

A100 80GB and RTX 4090 differ in memory capacity, native FP8 support and NVLink; an hourly price alone cannot resolve those requirements.

Updated 2026-10-07 · refreshed every 12 hours

Choose A100 80GB when its larger memory avoids an unsuitable configuration. Choose RTX 4090 for a fitting workload that needs native FP8. If the application requires NVLink, verify the A100 rental topology before booking.

Run a bounded test with the same model, precision, batch size and sequence length on each feasible option. Record peak memory, billed runtime and completed work; use the actual checkout rate to compare compute cost per completed job.

Can the job fit RTX 4090, and does it require FP8 or NVLink? Choose RTX 4090 for a fitting native-FP8 workload. Choose A100 80GB for supported work that needs its larger memory or verified NVLink topology. If neither meets all constraints, test a different configuration.

Which option meets your deadline and job budget in a representative test? Measure completion time first. The A100 80GB-to-RTX 4090 modeled cost-per-job ratio is 0.56; it uses specification-based assumptions and does not establish real runtime or a deadline.

Can the exact configuration launch under the rental terms your job needs? Confirm the GPU count, topology and availability at checkout. Use spot only after testing checkpoint recovery; if the required configuration cannot launch, reassess fit before substituting another GPU.

Today's prices

USD/hr · 1x GPU · prices grouped by provider and purchase model

Provider	A100 80GB	RTX 4090
Vast.ai	$0.38	$0.36
Hyperstack	$1.35 · Not reported	Not offered
Jarvislabs	$1.49 · Not reported	Not offered
RunPod	$1.59	$0.74
DataCrunch	$1.85	Not offered
Crusoe	$2.00 · Not reported	Not offered

Where the two parts differ

Specification	A100 80GB	RTX 4090
Memory	80 GB HBM2e	24 GB GDDR6X
Memory bandwidth	2039 GB/s	1008 GB/s
Dense BF16	312 TFLOPS	165 TFLOPS
Dense FP8	FP8 unsupported	330 TFLOPS
NVLink	600 GB/s	No NVLink
TDP	400 W	450 W

Prices are refreshed every 12 hours. Marlin matches your requirements across supported providers. Try Marlin →

1.06×

A100 80GB-to-RTX 4090 on-demand hourly price ratio. Below one favors the first GPU on hourly rate; above one favors the second.

0.56×

A100 80GB-to-RTX 4090 modeled cost-per-job ratio. Below one favors the first under the stated model; validate with measured runtime.

$277/mo

Continuous-use monthly baseline for one A100 80GB at its current on-demand minimum; scale the budget to your billed hours.

What your workload needs

Find your parameter count on the model's Hugging Face card. Serving maps to the inference rows, training to the fine-tuning rows. 1 listed workload is omitted because neither card has a currently eligible on-demand configuration at the required GPU count.

Workload	VRAM needed	A100 80GB	RTX 4090	Cheapest today
7B Q4 inference	4 GB	1-GPU configuration: $0.38/hr (In stock; observed 2026-10-07; price basis: Marketplace quote)	1-GPU configuration: $0.36/hr (In stock; observed 2026-10-07; price basis: Marketplace quote)	RTX 4090: 1 GPU at $0.36/hr
7B FP16 inference	17 GB	1-GPU configuration: $0.38/hr (In stock; observed 2026-10-07; price basis: Marketplace quote)	1-GPU configuration: $0.36/hr (In stock; observed 2026-10-07; price basis: Marketplace quote)	RTX 4090: 1 GPU at $0.36/hr
13B LoRA fine-tune	36 GB	1-GPU configuration: $0.38/hr (In stock; observed 2026-10-07; price basis: Marketplace quote)	No eligible 2-GPU configuration	A100 80GB: 1 GPU at $0.38/hr
70B FP8 training	154 GB	unsupported	No eligible 7-GPU configuration	No currently eligible on-demand configuration for RTX 4090 7-GPU configuration

What the numbers say

A100 80GB and RTX 4090 solve different constraints: the A100 provides more device memory and NVLink support, while RTX 4090 provides native FP8 support. A BF16 workload that fits the smaller device can be benchmarked on either; a workload requiring FP8 cannot use that as a reason to select A100.

A100 80GB has an on-demand minimum of $0.38/hr and RTX 4090 has an on-demand minimum of $0.36/hr. The A100 80GB-to-RTX 4090 on-demand price ratio is 1.06. When both configurations meet the same requirements, compare the current rates rather than assuming that either GPU is always cheaper. Spot listings have different interruption terms and are not the basis of that ratio.

Keep the precision and output-quality target explicit when comparing the two GPUs. A quantized RTX 4090 run and a BF16 A100 run answer different questions unless both meet the same acceptance target. For a multi-GPU plan, confirm the exact offered topology instead of assuming that adding devices pools their memory.

How to test the comparison

Hold the workload constant
Compare the same model, precision, batch size, sequence length and output-quality target. Changing these between GPUs changes the question being tested.
Measure the result you need
For serving, record latency and throughput at the intended concurrency. For training, record time for the same completed work. Check peak memory and failures in both cases.
Price the complete run
Multiply the full configuration's checkout rate by billed runtime. Compare storage, transfers and restart costs separately. A datasheet-based ratio is a screening model, not this measurement.

Before you rent

Data egress fees can raise the total beyond the GPU rate; verify them in the provider’s current network pricing before moving your dataset or outputs.

Exceeding one card’s VRAM forces model sharding across multiple GPUs, increasing both the GPU count and time lost to interconnect communication.

An interruptible rental can erase its price advantage when checkpoint gaps force work to repeat, so include restart time in the job-cost estimate.

Billing granularity can make a short experiment cost more than its runtime suggests; use the minimum charge on each provider’s pricing page when estimating the test budget.

Marlin matches your workload requirements to the lowest-priced suitable GPU across supported providers.

Memory fit and cost-per-job comparisons are models. Datasheet peaks do not establish application throughput; verify the listed configuration with your own workload. https://vast.ai/pricing · https://www.paperspace.com/pricing · https://www.tensordock.com/host-pricing · https://www.runpod.io/pricing · https://datacrunch.io/pricing · https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/a100/pdf/nvidia-a100-datasheet-us-nvidia-1758950-r4-web.pdf · https://www.nvidia.com/en-us/geforce/graphics-cards/40-series/rtx-4090/ · https://lambda.ai/service/gpu-cloud · https://www.hyperstack.cloud/gpu-pricing · https://jarvislabs.ai/pricing

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