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RTX 5080 vs RTX 5090 – The Real-World Gap for AI

Both are Blackwell. Both are fast. The 5090 costs more. How much performance do you actually get for the upgrade?

Blackwell silicon runs across the RTX 5080 and RTX 5090 on our dedicated GPU hosting. Both ship with FP8 tensor cores and GDDR7. The 5090 is meaningfully more expensive. For AI workloads, how much better does it actually perform?

Sections

Spec Gap

SpecRTX 5080RTX 5090
VRAM16 GB GDDR732 GB GDDR7
Memory bandwidth~960 GB/s~1,792 GB/s
CUDA cores~10,752~21,760
FP8 tensorYesYes
TDP360 W575 W

The 5090 has roughly double everything: VRAM, bandwidth, compute, power draw. On paper the 5090 is the 5080 plus fifty percent. In practice, the gap varies by workload.

The 16 GB vs 32 GB Split

This is the most important line in the table. 16 GB hosts 7B models comfortably at FP16, 13B models at INT8, and 30B models at INT4 with tight context. 32 GB hosts 13B at FP16, 30B at INT8, and opens 70B INT4 for single-card serving. If your target model sits above 13B, the 5090 is not an upgrade – it is the only one of the two that works. See can the 5090 run 70B and 70B INT4 VRAM.

Token Throughput

Where both cards fit a model, the 5090 runs roughly 60-80% faster per token on decode-heavy workloads because it has near-double the memory bandwidth. For prefill-heavy workloads (large prompts, RAG) the compute gap matters more and the 5090 advantage approaches 90-100%.

Workload50805090
Mistral 7B INT8 decode~85 t/s~145 t/s
Llama 3 8B INT4 decode~110 t/s~185 t/s
Llama 3 70B INT4Does not fit~38 t/s
SDXL 1024×1024 30 steps~2.3 s~1.4 s

Upgrade Only When It Pays Back

We host both cards on fixed UK monthly pricing – no need to guess from synthetic benchmarks.

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SDXL and Video

For pure image generation the 5090 runs about 40-50% faster than the 5080 per image. For video models where VRAM matters (CogVideoX, Hunyuan Video), only the 5090 is in the running. The 5080 runs out of memory on most modern video models. See our Hunyuan Video VRAM page.

When to Pick the 5090

Jump to the 5090 if any of these apply: your model is above 13B, you serve video, you batch many concurrent users, or you fine-tune. Stick with the 5080 if you are serving 7-13B LLMs with modest concurrency, running SDXL production at reasonable pace, or testing the economics before committing. The 5090 is not a luxury upgrade – it is a capability upgrade. Workloads either need it or they do not.

For step-up decisions see 6000 Pro vs dual 5090, and for value floor analysis see VRAM per pound.

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We benchmark, deploy, and optimise GPU infrastructure for AI workloads. All data in our guides comes from real-world testing on our UK-based dedicated GPU servers.

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