GPU MODELS / RTX 3050

RTX 3050 cloud GPU pricing

1 listings across 1 providers. Cheapest published rate: $0.030/GPU/hr at Salad. Sorted by per-GPU hourly price. Every row links to the provider's own published price.

WHAT IS THE RTX 3050

The 3050 is the cheapest Ampere card with tensor cores - the minimum hardware for modern ML frameworks' fast paths. In catalogs it is floor-price dev capacity: 8 GB and 224 GB/s limit it to small models and learning, but tensor cores put it ahead of any GTX card for ML.

MAKER
NVIDIA
ARCHITECTURE
Ampere
LAUNCHED
2022
MEMORY
8 GB GDDR6
MEMORY BANDWIDTH
224 GB/s
TENSOR COMPUTE
9.1 TFLOPS FP32; 3rd-gen tensor cores
POWER DRAW
130 W
INTERCONNECT
PCIe 4.0 x8

WHAT IT IS GOOD AT

Learning and dev
The cheapest tensor-core capacity - CUDA, mixed precision, small models.
7B inference
Barely - tight 4-bit with minimal context.
Serving or training
Not a fit - bandwidth and memory.

WHO SHOULD NOT RENT THE RTX 3050

Anything past small experiments.
Production inference of any size.
ProviderConfigVRAMLocation$/hr$/GPU/hrSource
SaladSaladRTX 3050 × 18 GBGlobal (distributed)$0.030$0.030receipt

THE RTX 3050 MARKET, BY THE NUMBERS

PROVIDERS
1
CONFIGURATIONS
1
MEDIAN $/GPU/HR
$0.03
SPREAD
1.0x

1 providers publish 1 RTX 3050 configurations on the panel today. Published per-GPU hourly rates run from $0.030 (Salad) to $0.03 (Salad), a 1x spread between the cheapest and the most expensive published rate for the same chip. The median listing sits at $0.03/GPU/hr. Rows are published catalog rates; stock flags appear per row where the provider reports them. All rates are on-demand - committed-use and reserved pricing is excluded.

RTX 3050 PRICE TREND, DAILY PANEL SNAPSHOTS

Across every RTX 3050 row on the panel, the daily floor held flat at $0.030/GPU/hr over 11 days of tracking. Snapshots run daily; the full history is public in the repo.

RTX 3050 PROVIDER NOTES
Salad · 1 config · 1 region
Sets the panel floor for this model.
from $0.030/hr
BUYING RTX 3050: WHAT THE PANEL SAYS

At the current floor, one RTX 3050 running around the clock costs about $22 a month (730 hours of on-demand arithmetic). Compare the alternatives below before committing - the same budget often buys more than one chip class.

RTX 3050 VS THE ALTERNATIVES

RTX 3050 vs GTX 1660 SUPER
Same price floor, but the 3050's tensor cores make it the only one of the two usable for ML. For transcoding they are equivalent.
RTX 3050 vs RTX 3060
The 3060's 12 GB and 360 GB/s open real workloads for a modest premium. The 3050 is for learning, the 3060 for doing.

Compare live rates: RTX 3050 vs GTX 1660 SUPER · RTX 3050 vs RTX 3060

RTX 3050 PRICING FAQ

What is the cheapest RTX 3050 cloud GPU right now?
The cheapest published RTX 3050 rate on the panel is $0.030 per GPU-hour at Salad (RTX 3050 x 1, Global (distributed)). Every price links to the provider's own published rate.
How much does a RTX 3050 cost per hour?
Across 1 providers tracked today, published per-GPU hourly rates for RTX 3050 run from $0.03 to $0.03, with a median of $0.03. Committed-use and reserved rates are excluded; everything shown is on-demand.
How many providers rent RTX 3050 GPUs?
1 providers publish 1 distinct RTX 3050 configurations on Compute Cafe. The panel shows published rates; stock flags appear per row where the provider reports them.
Are RTX 3050 prices going up or down?
Over the 11 days Compute Cafe has tracked the panel, the RTX 3050 floor is holding flat: $0.030 to $0.030/GPU/hr (+0.0%). Daily snapshots are public in the repo, so the trend is auditable.
What does a RTX 3050 cost per month?
At the current floor of $0.030/GPU/hr, a RTX 3050 running 24/7 costs about $22 per month (730 hours of on-demand arithmetic on the cheapest published rate). Committed-use contracts can price lower; the panel tracks on-demand rates only.
Is the RTX 3050 enough for ML?
For learning, yes - it is the cheapest card with tensor cores. For real workloads, its 8 GB and 224 GB/s mean the 3060 12 GB is the practical minimum.

See also alternatives to the RTX 3050 · cheapest GPU-hour per model · inference chips · training chips · by location