RTX PRO 4000 Blackwell 24 GB for Blender
High-end Blackwell 2.0 GPU built for large Blender scenes and heavy assets where memory headroom matters most.
Last updated: October 1, 2026
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$3,194.00
Checked Oct 2, 2026
- Blender Cycles score
- 6,587
- 1.8× slower than
- VRAM
- 24 GB
- More capacity for heavy scenes
- Released
- 2025
- Render support
- CUDA, OpenCL
- Power draw (TDP)
- 140 W
- Suggested system PSU
- 300 W
Technical specifications
GPU
- ArchitectureBlackwell 2.0
- CUDA cores8,960
- Tensor cores280
- RT cores70
Memory
- TypeGDDR7
- Bandwidth672 GB/s
- Bus width192-bit
Clocks & manufacturing
- Boost clock2055 MHz
- Base clock1230 MHz
- Process size5 nm
- GPU chipGB203
Power & PSU sources
GPU power ratings
TDP: 140 W
Secondary source: RightNow GPU Database / TechPowerUp ↗ · Checked Sep 23, 2026 · Reference card
System power supply
Suggested PSU: 300 W
Secondary source: RightNow GPU Database / TechPowerUp ↗ · Checked Sep 23, 2026 · Reference system
Third-party source suggestion; not the manufacturer’s minimum system requirement.
GPU power ratings and whole-system PSU recommendations measure different things. Check the exact card and the source’s system assumptions.
RTX PRO 4000 Blackwell 24 GB Blender benchmarks
Estimated time to render one benchmark frame · Lower is faster.
Blender 5.2.0 · OptiX · 7 runs
About these estimates
Times estimate one frame of each benchmark scene from the same runs, Blender version and backend as the displayed Cycles score. The calculation uses 240 samples for Junkshop, 256 for Monster and 300 for Classroom, plus a 19% estimation buffer. Actual project render times vary. Results from different Blender versions may not be directly comparable.
Is RTX PRO 4000 Blackwell 24 GB 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
- Useful for frequent renders and faster lighting/material iterations.
Who should choose it
- High-end Blackwell 2.0 GPU built for large Blender scenes and heavy assets where memory headroom matters most.
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