Pipeline Brief // CUDA Out of Memory in 3D RenderingA CUDA out of memory error during a render means the scene, textures and buffers need more VRAM t
Pipeline Brief // CUDA Out of Memory in 3D Rendering
A CUDA out of memory error during a render means the scene, textures and buffers need more VRAM than the GPU has, and the fix is to load less or use a card with more memory.
- Textures First: An uncompressed 8K RGBA map is about 256 MiB against 16 MiB for 2K, a 16x difference, so texture size is usually the cheapest cut.
- Buffers Add Up: A 4K float RGBA render pass is about 127 MiB, so every extra AOV costs memory on top of the scene.
- Fallbacks Are Slower: Blender and Redshift can use system memory when VRAM fills, which avoids the crash but slows the frame.
- Production Verdict: Trim first, then decide between a larger card and rented GPUs using our render farm ranking.
A CUDA out of memory error means the render engine tried to load more geometry, textures and buffers into VRAM than the GPU holds, so the render fails. A faster card with the same memory fails the same way. This guide shows what fills VRAM, how to measure it, and the fixes in order of cost.
What is filling your VRAM during a render?
Five things commonly fill GPU memory: textures, geometry, render buffers, the denoiser and other applications. The figures below are arithmetic from uncompressed sizes, so real usage depends on texture formats, compression and the render engine.
| What uses VRAM | Why it adds up | Quickest cut |
|---|---|---|
| Oversized textures | An 8192 x 8192 RGBA 8-bit map is about 256 MiB uncompressed; 2048 x 2048 is about 16 MiB, so 8K is 16x larger | Use 2K or 4K maps on objects far from the camera |
| Dense geometry and subdivision | Redshift documents roughly 60 MB per million triangles for typical meshes, and render-time subdivision multiplies the count | Lower subdivision, use proxies, instance repeated objects |
| Render passes (AOVs) | A 3840 x 2160 RGBA 32-bit float buffer is about 127 MiB per pass | Remove passes you do not need in compositing |
| Denoiser | Needs working memory on top of the render; the amount varies by engine | Try a lighter mode or denoise as a separate step |
| Other GPU apps | Redshift reserves 90 percent of free GPU memory by default, leaving the remainder to the OS and other apps | Close other GPU-heavy apps before a long render |
The 60 MB per million triangles and 90 percent default figures come from the Maxon Redshift Memory documentation. Texture and buffer sizes are our own calculations, labelled as estimates.
How do you fix a CUDA out of memory error?
Fix it in order of cost: cut texture size, close other apps, reduce geometry load, trim passes, then change the denoiser if the crash happens at the end of a frame. If the scene still does not fit, use a fallback or more memory.
| Step | Action | Notes |
|---|---|---|
| 1 | Right-size textures | Usually the largest single gain; use the Simplify texture limit in Blender |
| 2 | Close other apps using the GPU | Browsers and viewers hold VRAM |
| 3 | Lower subdivision, instance repeats | Proxies help for dense assets |
| 4 | Remove unneeded AOVs | Each pass holds its own buffer |
| 5 | Change denoiser mode | If the crash comes at the end of an otherwise fine frame |
| 6 | Use out-of-core or more VRAM | See below |
Blender’s Simplify settings include a texture size limit that scales textures down to a chosen maximum. For the full list of memory cuts in Blender, see our guide to Blender crashing mid-render.
What happens when the scene does not fit?
Some engines spill data into system memory. The Blender manual says that for CUDA, OptiX, HIP and Metal devices Blender will automatically try to use system memory when GPU memory is full, with a performance impact that is usually still faster than CPU rendering. Redshift describes out-of-core texturing and geometry as features of its memory system, with details on the Maxon Redshift Memory page. Use it for the occasional heavy frame, not a whole sequence, because data moving over the PCIe bus is slower than data held in VRAM (our reading of how out-of-core works).
When does the scene need a bigger card?
If trimming costs quality you need, or the scene still fails, you need more VRAM. Two GPUs usually do not help, because the Blender manual says each GPU can only access its own memory, except NVIDIA cards connected with NVLink. Compare your options in what to do when a scene needs 20GB and you have 8GB, and see our RTX 5090 review for the 32 GB option. For occasional heavy jobs, renting GPU time can cost less than buying; compare providers in our render farm ranking. Our VRAM and system RAM guide explains how different engines use each.
FAQ
Does a faster GPU fix CUDA out of memory?
No. The error is a capacity problem, so a faster card with the same amount of VRAM fails in the same way. Use less memory in the scene or use a card with more VRAM.
How do I reduce VRAM usage when rendering?
Right-size textures first, then close other GPU apps, lower render-time subdivision, instance repeated geometry and remove render passes you do not need for compositing.
What is out-of-core rendering?
Out-of-core rendering lets the renderer keep some data in system memory when VRAM is full. It avoids the crash but slows the frame, so frequent use suggests the scene has outgrown the card.
Does adding a second GPU add VRAM?
Typically no. The Blender manual says each GPU can only access its own memory, with the exception of NVIDIA GPUs connected with NVLink.
Sources: Maxon Redshift Memory documentation, Blender Manual, GPU rendering and Simplify (Blender 5.2 LTS manual, checked October 2026).
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