RTX A5500 for Blender

Blender score 4,925
Fast
High VRAM
Workstation GPU

High-end Ampere GPU built for large Blender scenes, heavier assets, and very fast Cycles rendering.

Last updated: May 26, 2026

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Blender benchmark score

4,925

Solid mid-range speed for everyday rendering and moderate scenes.

VRAM

24 GB

Plenty of room for large scenes, dense geometry, and 4K–8K textures.

CUDA cores

10,240

High core count for strong parallel rendering throughput.

Architecture

Ampere

Previous-generation design — still competitive, especially at higher VRAM tiers.

Memory bandwidth

768 GB/s

Strong bandwidth for most Blender rendering scenarios.

Boost clock

1665 MHz

Lower clock speed — typical of older or workstation-class GPUs.

Render support

OptiX, CUDA

OptiX is typically the fastest option; CUDA provides a reliable fallback.

TDP

230 W

Relatively efficient — manageable in most desktop builds.

Release year

2022

More technical details

Core specs

  • Tensor cores: 320
  • RT cores: 80
  • Base clock: 1080 MHz
  • Process size: 8 nm

Memory specs

  • Memory type: GDDR6
  • Memory bus: 384-bit

Benchmark performance

This chart estimates how many seconds this GPU takes to render one frame of each standard Blender benchmark scene, so you can compare practical rendering speed at a glance.

Blender score 4,925
seconds
Estimated time to render one benchmark frame. Lower is faster.
OptiX
Junkshop
12.12s
Monster
8.07s
Classroom
17.19s
0s20s

These are single-frame estimates derived from Blender Open Data benchmark medians at the scene sample counts, not full-animation render times or guarantees for every real project.

View Blender Open Data source

Is RTX A5500 good for Blender?

A concise editorial read on where this GPU looks strong, the tradeoffs to keep in mind, and who it suits best.

What stands out

  • 24 GB GDDR6 VRAM
  • Ampere architecture
  • High memory bandwidth of 768 GB/s
  • Exceptional performance with 10240 CUDA cores
  • Enhanced ray tracing capabilities with 80 RT cores
  • Efficient rendering with 320 Tensor cores

Tradeoffs to know

  • High power consumption typical of workstation GPUs
  • Potential overkill for smaller, less complex projects

Who should choose it

  • Need for high VRAM capacity
  • Desire for cutting-edge rendering capabilities
  • Preference for robust workstation performance

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