GeForce RTX 5080
NVIDIA · Consumer GPU · 2025
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Price checked Jul 23, 2026
Performance Benchmarks
Image Generation all sourced rows →
| Model | Metric | Value | Source |
|---|---|---|---|
| SDXL Turbo FP16 | images per minute |
65
img/min
ComfyUI · 2025-06-01
|
Independent benchmark TechPowerUp GPU Reviews ↗ |
|
Stable Diffusion 1.5
FP16 Standardized UL Procyon suite; same lab platform (ThreadRipper 7980X, driver 571.86); 1.344 s/image |
procyon image overall score |
4,650
score
UL Procyon AI Image Generation · 2025-01-29
|
Independent benchmark StorageReview GPU Reviews ↗ |
|
Stable Diffusion 1.5 INT8
INT8 Standardized UL Procyon suite; same lab platform (ThreadRipper 7980X, driver 571.86); 0.561 s/image |
procyon image overall score |
55,683
score
UL Procyon AI Image Generation · 2025-01-29
|
Independent benchmark StorageReview GPU Reviews ↗ |
|
Stable Diffusion XL
FP16 Standardized UL Procyon suite; same lab platform (ThreadRipper 7980X, driver 571.86); 8.808 s/image |
procyon image overall score |
4,257
score
UL Procyon AI Image Generation · 2025-01-29
|
Independent benchmark StorageReview GPU Reviews ↗ |
LLM Inference all sourced rows →
| Model | Metric | Value | Source |
|---|---|---|---|
|
Llama-2-13B
Standardized UL Procyon suite; same lab platform (ThreadRipper 7980X, driver 571.86); output rate 83.653 tok/s |
procyon text overall score |
4,790
score
UL Procyon AI Text Generation (TensorRT) · 2025-01-29
|
Independent benchmark StorageReview GPU Reviews ↗ |
|
Llama-3-8B
Standardized UL Procyon suite; same lab platform (ThreadRipper 7980X, driver 571.86); output rate 136.177 tok/s |
procyon text overall score |
4,424
score
UL Procyon AI Text Generation (TensorRT) · 2025-01-29
|
Independent benchmark StorageReview GPU Reviews ↗ |
|
Llama-3.1-8B
Q4_K_M Token generation: single user, batch 1; source measured 5090=213 / 4090=127 on same rig, within 2% of myaihardware baseline |
tokens per second |
132
tok/s
llama.cpp via Ollama · 2026-08-01
|
Unverified community LocalAI Master GPU Benchmarks ↗ |
|
Llama-3.1-8B
Q4_K_M Prompt processing: ~5,200 tok/s reported (approximate, batch 1) |
prompt tokens per second |
5,200
tok/s
llama.cpp via Ollama · 2026-08-01
|
Unverified community LocalAI Master GPU Benchmarks ↗ |
|
Mistral-7B
Standardized UL Procyon suite; same lab platform (ThreadRipper 7980X, driver 571.86); output rate 163.598 tok/s |
procyon text overall score |
4,635
score
UL Procyon AI Text Generation (TensorRT) · 2025-01-29
|
Independent benchmark StorageReview GPU Reviews ↗ |
|
Phi-3.5-mini
Standardized UL Procyon suite; same lab platform (ThreadRipper 7980X, driver 571.86); output rate 209.459 tok/s |
procyon text overall score |
4,400
score
UL Procyon AI Text Generation (TensorRT) · 2025-01-29
|
Independent benchmark StorageReview GPU Reviews ↗ |
|
Qwen3-8B
Q4_K_XL Token generation: 16K context, batch 1, Ubuntu 24.04, on-hardware lab measurement |
tokens per second |
94.1
tok/s
llama.cpp llama-bench, CUDA 12.8 · 2025-12-09
|
Unverified community Hardware Corner LLM GPU Rankings ↗ |
Full Specifications
Related GPUs
Common Questions
Can the GeForce RTX 5080 run local LLMs?
Yes, if the model fits in its 16 GB of memory — VRAM capacity decides which models load at all, while its 960 GB/s of bandwidth decides how fast tokens generate. 8B-class models at Q4 quantization fit comfortably; larger 70B-class models need a card with more VRAM.
How much VRAM does the GeForce RTX 5080 have?
GeForce RTX 5080 has 16 GB of video memory with 960 GB/s of memory bandwidth and a 360 W TDP , per the specification values in our hardware database.
Is the GeForce RTX 5080 worth it for AI workloads?
At a $999 MSRP, its value depends on whether your models fit in 16 GB. Compare its VRAM and bandwidth against your target models with our VRAM calculator, or see how it stacks up in head-to-head comparisons.
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