RTX 2080 SUPER for Blender
Turing GPU best suited to lighter Blender scenes, learning workflows, and budget-conscious rendering setups.
Last updated: May 26, 2026
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2,398
Entry-level speed — fine for learning and lighter scenes.
8 GB
Enough for moderate scenes; heavy assets may push against the limit.
3,072
Lower core count — adequate for lighter rendering workloads.
Turing
Older architecture — introduced hardware ray tracing for NVIDIA GPUs.
495.9 GB/s
Moderate bandwidth — sufficient for standard rendering workloads.
1815 MHz
Lower clock speed — typical of older or workstation-class GPUs.
OptiX, CUDA
OptiX is typically the fastest option; CUDA provides a reliable fallback.
250 W
Moderate power needs — standard workstation PSU and cooling should be fine.
2019
More technical details
Core specs
- Tensor cores: 384
- RT cores: 48
- Base clock: 1650 MHz
- Process size: 12 nm
Memory specs
- Memory type: GDDR6
- Memory bus: 256-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.
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 sourceIs RTX 2080 SUPER 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
- Turing architecture with 3072 CUDA cores
- 12 nm process size enhancing efficiency
- Boost clock of 1815 MHz for faster processing
- 495.9 GB/s memory bandwidth supporting high-speed data transfer
Tradeoffs to know
- Limited to 8 GB VRAM, which may not suffice for large projects
- Not the latest generation, lacking some modern features
Who should choose it
- Reliable rendering performance for mid-range projects
- Cost-effective option for Blender users not requiring the latest features
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