H200 vs RTX 4000 SFF Ada: Specs, VRAM & Price

Short answer: choose the H200 when 141 GB of VRAM is the gating requirement. Choose the RTX 4000 SFF Ada when 20 GB is enough for the workload and the lower hourly rate points that way.

The H200 has 141 GB of VRAM; the RTX 4000 SFF Ada has 20 GB.

You can rent both by the hour, no purchase required. H200 from $3.95/GPU/hr; RTX 4000 SFF Ada from $0.198/GPU/hr. The RTX 4000 SFF Ada is 95% cheaper at the entry rate.

H200

Good for training and serving frontier-scale LLMs

$3.95/hr
Lowest / GPU
$5.82/hr
Median / GPU
141 GB
VRAM
Hopper
Architecture

RTX 4000 SFF Ada

Good for inference and light fine-tuning workloads

$0.198/hr
Lowest / GPU
$0.198/hr
Median / GPU
20 GB
VRAM
Ada Lovelace
Architecture

Last updated: 2026-10-10 21:00:22 UTCRefreshes hourly

Specs side by side

SpecH200RTX 4000 SFF Ada
VRAM141 GB20 GB
Memory bandwidth4.8 TB/s–
ArchitectureHopperAda Lovelace
Compute capability9.08.9
Precisions in hardwareFP32, FP16, BF16, FP8, INT4FP32, FP16, BF16, FP8, INT4
Peak FP16/BF16 tensor TFLOPS989 TFLOPS–
Peak FP8 tensor TFLOPS1,979 TFLOPS–
NVLink / multi-GPU interconnectNVLink 4, 900 GB/s bidirectional–
Max board power (TDP)Up to 700W (configurable)–
Form factorSXM–
Regions51

On-demand price

RateH200RTX 4000 SFF Ada
Lowest per GPU/hr$3.98/GPU/hr$0.198/GPU/hr (cheapest overall)

Which is better for AI: H200 or RTX 4000 SFF Ada?

Choose the H200 when 141 GB of VRAM is the gating requirement. Choose the RTX 4000 SFF Ada when 20 GB is enough for the workload and the lower hourly rate points that way.

H200 vs RTX 4000 SFF Ada: common questions

Is the H200 or the RTX 4000 SFF Ada better for AI?

Short answer: choose the H200 when 141 GB of VRAM is the gating requirement. Choose the RTX 4000 SFF Ada when 20 GB is enough for the workload and the lower hourly rate points that way.

Is the H200 or the RTX 4000 SFF Ada cheaper to rent?

On Aquanode's live marketplace the H200 starts at $3.95/GPU/hr (median $5.82/GPU/hr) and the RTX 4000 SFF Ada starts at $0.198/GPU/hr (median $0.198/GPU/hr). The RTX 4000 SFF Ada is the cheaper of the two at the entry rate, by 95%.

What is the difference between the H200 and the RTX 4000 SFF Ada?

The H200 has 141 GB of VRAM against the RTX 4000 SFF Ada's 20 GB; the H200 is a Hopper part and the RTX 4000 SFF Ada is Ada Lovelace (compute capability 9.0 vs 8.9); both run BF16, FP8, INT4 workloads in hardware. On price, the H200 lists from $3.95/GPU/hr and the RTX 4000 SFF Ada from $0.198/GPU/hr.

How widely available are the H200 and the RTX 4000 SFF Ada?

The H200 is listed in 5 regions and the RTX 4000 SFF Ada in 1 region right now.

How much does 1,000 GPU-hours cost on the H200 vs the RTX 4000 SFF Ada?

At the lowest rates listed today, 1,000 GPU-hours costs $3,949 on the H200 and $198 on the RTX 4000 SFF Ada, a difference of $3,751 for the same runtime. Rates are per GPU per hour and update hourly.

How much VRAM does the H200 have compared to the RTX 4000 SFF Ada?

The H200 has 141 GB of VRAM; the RTX 4000 SFF Ada has 20 GB.

How this comparison is calculated

Every price is normalized to a per-GPU hourly rate using the same pipeline as every other pricing surface on Aquanode, and only the cheapest qualifying offer per provider is shown. A dash means that provider does not currently list that GPU.

Architecture, compute capability and supported precisions come from each vendor's published datasheet for that generation, not from the marketplace feed. This page regenerates at most once per hour.

Memory bandwidth, tensor TFLOPS, NVLink/interconnect and max board power are the same verified-from-datasheet figures shown on each model's own H200 page and RTX 4000 SFF Ada page, which link the primary vendor source for that model. A dash here means Aquanode hasn't verified that figure from a primary source yet, never a guess.

Go further

Check what fits in each card's memory with the H200 VRAM calculator and the RTX 4000 SFF Ada VRAM calculator, see vendor-published throughput in the GPU benchmarks and specs table, or browse every model by generation in the GPU index.

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