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

We checked current provider listings and official hardware specifications to show when A100 80GB or RTX 4090 is the better fit for your workload.

Updated 2026-08-23 · refreshed daily

Choose A100 80GB when its larger memory avoids a multi-GPU setup, choose RTX 4090 when the workload fits on one card at an A-to-B on-demand price ratio of 2.14, except when you need NVLink.

Before committing, run the same representative job once on each GPU at the live table’s on-demand minimums of $0.60 for A100 80GB and $0.28 for RTX 4090, then compare the actual cost per completed job.

How much GPU memory does your workload require? Choose RTX 4090 for FP8, BF16, or FP32 workloads within 24GB VRAM; for BF16 or FP32 workloads within 80GB VRAM that exceeds the smaller card’s memory ceiling, choose A100 80GB, and use a multi-GPU configuration beyond that.
Is finishing sooner worth the difference in per-job cost? If finishing sooner matters, choose A100 80GB because its effective cost-per-job ratio of 1.13 indicates a slight modeled cost advantage over RTX 4090.
Is the recommended GPU available when your job must start? If the recommended GPU is unavailable, run one representative job as a small test rental on the available alternative.

Today's prices

USD/hr · 1× GPU · lowest on-demand price per provider

ProviderA100 80GBRTX 4090
Vast.ai $0.60 $0.28
Hyperstack $1.35 · Not reported Not offered
RunPod $1.39 $0.74
Jarvislabs $1.49 · Not reported Not offered
DataCrunch $1.79 Not offered
Crusoe $2.00 · Not reported Not offered

Prices refresh daily. Marlin always books the cheapest available. Try Marlin →
2.14×
On-demand price ratio favoring RTX 4090 when its memory is sufficient
1.13×
A100 80GB has a slight modeled cost-per-job edge at on-demand rates
$438/mo
Monthly budget baseline for continuously running A100 80GB at its on-demand minimum

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.

WorkloadVRAM neededA100 80GBRTX 4090Cheapest today
70B Q4 inference 42 GB 1× $0.60/hr 2× $0.28/hr RTX 4090 ×2 → $0.56/hr (est.)
70B FP16 inference 168 GB 3× $0.60/hr 7× $0.28/hr A100 80GB ×3 → $1.8/hr (est.)
70B QLoRA 46 GB 1× $0.60/hr 2× $0.28/hr RTX 4090 ×2 → $0.56/hr (est.)
7B full fine-tune 112 GB 2× $0.60/hr 5× $0.28/hr A100 80GB ×2 → $1.2/hr (est.)
70B FP8 training 154 GB unsupported 7× $0.28/hr RTX 4090 ×7 → $1.96/hr (est.)
Downshift recommendation 42 GB 1× $0.60/hr 2× $0.28/hr A100 80GB ×1 → $0.6/hr

What the numbers say

A100 80GB has an on-demand minimum of $0.60, while RTX 4090 has an on-demand minimum of $0.28. That makes RTX 4090 the direct price choice when the workload fits on one card, but A100 80GB can be the better job-level value when its larger memory avoids a multi-GPU setup.

A100 80GB looks stronger for compute-bound BF16 work: vendor peak specifications imply an A-to-B performance ratio of 1.89, producing a modeled on-demand cost-per-job ratio of 1.13 versus RTX 4090. Actual throughput may differ with the model, software stack, and utilization.

A100 80GB is suited to BF16 or FP32 workloads within 80GB VRAM, while RTX 4090 covers FP8, BF16, or FP32 workloads within 24GB VRAM. FP8 therefore directs you to RTX 4090, while BF16 or FP32 jobs that exceed its memory ceiling but fit on A100 80GB favor the larger card; otherwise, RTX 4090 is the rational on-demand price choice.

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 available across major cloud providers.

Source coverage is limited to the listed provider pricing pages and official hardware specifications, with freshness shown separately on the page. Prices and availability can change quickly, while performance and workload-cost comparisons are modeled estimates whose assumptions may not match measured results. 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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