Compute Comparison
NVIDIABlackwell2025

RTX 5080

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Current median: $0.65/hr across 3 providers (observed), 0.00 (0.0%) vs yesterday. Typical range: $0.60–$0.67/hr (P10–P90). 30-day trend unlocks after 30 days of captures

TDP 360W · 275.4 TFLOPS · 16GB VRAM · 960 GB/s bandwidth

The RTX 5080 has a 360W TDP, 275.4 TFLOPS of FP16 compute, 16GB of GDDR7 VRAM, 960 GB/s memory bandwidth.

Strong mid-range Blackwell. 16GB GDDR7 limits model size but excellent FP32 per dollar. Lower TDP than 5090.

VRAM
16GB
GDDR7
FP16
275.4
TFLOPS
Bandwidth
960.0
GB/s
TDP
360W
power
Best for:Budget consumer inferenceSmall model fine-tuningCost-efficient serving

RTX 5080 currently rents for a median of $0.65/hr across 3 providers (observed on-demand prices). RTX 5080 has 16GB of memory. Compare its specs and listed cloud rental prices below. The workload must fit in VRAM with room for runtime memory; a listed price does not confirm stock.

RTX 5080 Overview

The RTX 5080 brings Blackwell architecture to a more attainable consumer tier, with 16GB of GDDR7, 275.4 TFLOPS of FP16/BF16 throughput, and a 360W board power target. It is a fast accelerator for compact models, but its memory capacity—not arithmetic capability—sets the practical boundary for many AI jobs.

GDDR7 delivers 960 GB/s of bandwidth, a substantial improvement for a 16GB-class card and useful for responsive inference on models that fit. Capacity remains the constraint: 16GB is comfortable for smaller models and quantized workloads, while larger FP16 models and large KV caches quickly require a different tier of hardware.

The RTX 5080 suits experimentation, small-model fine-tuning, image generation, and economical inference fleets where individual requests fit on one device. It lacks ECC and NVLink, so it is not a replacement for professional or HBM-equipped GPUs in reliability-critical or memory-scaled deployments.

Memory

VRAM16 GB
Memory TypeGDDR7
Bandwidth960 GB/s

Compute Performance

FP32137.7 TFLOPS
FP16275.4 TFLOPS
BF16275.4 TFLOPS
INT8551 TOPS

Hardware Specifications

Chip

ArchitectureGB203
GenerationBlackwell
Process NodeTSMC 4NP
Transistors45.6B
Die Size378 mm²
Release DateJanuary 30, 2025
Launch MSRP$999

Processors

CUDA / Shader Cores10,752
Tensor Cores336
RT Cores84

Clocks

Base Clock2,295 MHz
Boost Clock2,617 MHz

Memory

VRAM16 GB
Memory TypeGDDR7
Memory Bus256-bit
Bandwidth960 GB/s
L2 Cache64 MB

Power

TDP360 W
InterconnectPCIe 5.0

Relative Performance

FP16 Compute4%
VRAM Capacity6%
Mem Bandwidth6%

Relative to highest-spec GPU in database

Limitations

Only 16GB VRAM limits models to ~13B parameters at FP16
No NVLink — single-card VRAM ceiling
Consumer-grade reliability, no ECC memory

Live Cloud PricingOn-demand hourly rates

Live4 providers · 111% price spread
ProviderOn-DemandSpotRegionAvailability
$0.28/hr—CHunknown
$0.68/hr—EU/USunknown
$0.65/hr—Variousunknown
$0.59/hr—USunknown
Cheapest / month
$204
$0.28/hr × 730h
Median / month
$475
at median price
Spot savings
N/A
vs on-demand (best)

Job Cost Estimator

At median $0.65/hr across 3 providers (observed on-demand). Spot pricing typically 40–70% lower.

7B LLM fine-tune
8× GPU, 24 h · Full fine-tune, single node
$125
spot ~$56
70B LLM fine-tune
64× GPU, 72 h · Multi-node, 3-day run
$3.0k
spot ~$1.3k
Inference server
1× GPU, 730 h · 1 month continuous
$475
spot ~$214
Image gen batch
4× GPU, 8 h · Batch generation job
$21
spot ~$9

Estimates only. Actual cost depends on provider, region, availability, and utilization. Use the GPU cost calculator for custom inputs.

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Use Case Guidance

Budget consumer inference
Small model fine-tuning
Cost-efficient serving

LLM Model Size Guidance

Max model (FP16)~8Bparameters at FP16 precision
Max model (INT8)~16Bparameters at INT8 precision
Max model (INT4)~32Bparameters at INT4/GGUF

Estimates only. Actual capacity depends on context length, KV cache, and framework overhead.

Related Guides

LLM APIs Running on This GPU Class

Providers that serve frontier LLM inference on Blackwell-class hardware.

Browse all 42 LLM models

RTX 5080 vs Alternatives — Spec Comparison

SpecRTX 5080 thisRTX PRO 6000 BlackwellA100 80GBA100 40GB
VRAM16GB GDDR796GB GDDR7▲80GB HBM2e40GB HBM2e
Memory Bandwidth960 GB/s1792 GB/s2000 GB/s▲1555 GB/s
FP16 TFLOPS275.4250312▲312▲
BF16 TFLOPS275.4250312▲312▲
FP8 TFLOPS—500▲——
INT8 TOPS551500624▲624▲
TDP360W300W400W▲300W
Process NodeTSMC 4NPTSMC 4NPTSMC 7nm▲TSMC 7nm▲
ArchitectureGB203▲GB202GA100GA100
Release Year2025▲2025▲20202020
Max model (FP16)~8B params~48B params▲~40B params~20B params
Max model (INT4)~32B params~192B params▲~160B params~80B params
▲ indicates best value in row · FP16/BF16 TFLOPS at full precision · Max model estimates at 2 bytes/param (FP16) and 0.5 bytes/param (INT4)Full side-by-side comparison

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RTX 5080 Frequently Asked Questions

What is the RTX 5080 TDP?

The RTX 5080 has a TDP (Thermal Design Power) of 360W.

How many TFLOPS does the RTX 5080 have?

The RTX 5080 delivers 275.4 TFLOPS of FP16 compute and 275.4 TFLOPS BF16.

How much VRAM does the RTX 5080 have?

The RTX 5080 has 16GB of GDDR7 VRAM.

What is the RTX 5080's memory bandwidth?

The RTX 5080 has a memory bandwidth of 960 GB/s.

RTX 5080 User Reviews

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