CUDA - Revision history

Smudgebun: /* Enabling CUDA In Packages */ Improved tips on installing large CUDA packages without a cache

2026-05-11T19:24:00Z

Enabling CUDA In Packages: Improved tips on installing large CUDA packages without a cache

← Older revision		Revision as of 19:24, 11 May 2026
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	Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.		Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.

	{{info\|If you will be using <code>cudaSupport</code> in packages, it is recommended you utilize a [[#Setting up CUDA Binary Cache\|CUDA ~~Binary Cache~~]].}}		{{info\|If you will be using <code>cudaSupport</code> in packages, it is recommended you utilize a [[#Setting up CUDA Binary Cache\|CUDA binary cache]].}}

	Without a [[#Setting up CUDA Binary Cache\|CUDA ~~Cache~~]], any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages.		Without a [[#Setting up CUDA Binary Cache\|CUDA cache]], any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages.

	For larger programs like Blender, that process can be very resource-intensive. If ~~you know~~ you are installing a large package ~~and~~ are not using a cache, on older or weaker hardware it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a ~~crash~~ from resource limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] page.		For larger programs like Blender, that process can be very resource-intensive. If you are installing large CUDA-enabled package(s) that either are not cached or you are not using a cache, then (especially on older or weaker hardware) it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a system freeze from resource limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] manual page.

			If you don't want to deal with the increased time that compilation will take when <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> are set below maximum, you can also try simply closing other running processes to see if that frees up enough resources for compilation to be successful.

	→ For specifics on setting up Blender with CUDA (and OptiX) see: [[Blender#CUDA & OptiX]].		→ For specifics on setting up Blender with CUDA (and OptiX) see: [[Blender#CUDA & OptiX]].

Smudgebun: /* Enabling CUDA In Packages */ Slight rephrasing

2026-05-11T17:26:32Z

Enabling CUDA In Packages: Slight rephrasing

← Older revision		Revision as of 17:26, 11 May 2026
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	Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.		Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.

	{{info\|If you will be using <code>cudaSupport</code> in packages, it is ~~highly~~ recommended you utilize ~~the~~ [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]].}}		{{info\|If you will be using <code>cudaSupport</code> in packages, it is recommended you utilize a [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]].}}

	Without ~~the~~ [[#Setting up CUDA Binary Cache\|CUDA Cache]], any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages.		Without a [[#Setting up CUDA Binary Cache\|CUDA Cache]], any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages.

	For larger programs like Blender, that process can be very resource-intensive. If you know you are installing a large package and ~~cannot use the~~ cache, it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a crash from ~~memory~~ limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] page.		For larger programs like Blender, that process can be very resource-intensive. If you know you are installing a large package and are not using a cache, on older or weaker hardware it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a crash from resource limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] page.

	→ For specifics on setting up Blender with CUDA (and OptiX) see: [[Blender#CUDA & OptiX]].		→ For specifics on setting up Blender with CUDA (and OptiX) see: [[Blender#CUDA & OptiX]].

Smudgebun: /* Enabling CUDA In Packages */Changed a reference to the cache from plaintext to an anchor link

2026-04-13T21:44:35Z

Enabling CUDA In Packages: Changed a reference to the cache from plaintext to an anchor link

← Older revision		Revision as of 21:44, 13 April 2026
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	{{info\|If you will be using <code>cudaSupport</code> in packages, it is highly recommended you utilize the [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]].}}		{{info\|If you will be using <code>cudaSupport</code> in packages, it is highly recommended you utilize the [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]].}}

	Without the CUDA Cache, any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages.		Without the [[#Setting up CUDA Binary Cache\|CUDA Cache]], any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages.

	For larger programs like Blender, that process can be very resource-intensive. If you know you are installing a large package and cannot use the cache, it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a crash from memory limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] page.		For larger programs like Blender, that process can be very resource-intensive. If you know you are installing a large package and cannot use the cache, it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a crash from memory limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] page.

Smudgebun: /* Driver Installation */Added correct lang for syntax highlighting

2026-04-11T14:08:55Z

Driver Installation: Added correct lang for syntax highlighting

← Older revision		Revision as of 14:08, 11 April 2026
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	Assuming you've followed the [[NVIDIA]] page correctly, and have a CUDA compatible GPU, you shouldn't need to do any further configuration. You can confirm your CUDA version by running the following command in your terminal.		Assuming you've followed the [[NVIDIA]] page correctly, and have a CUDA compatible GPU, you shouldn't need to do any further configuration. You can confirm your CUDA version by running the following command in your terminal.

	{{code\|lang=sh\|line=no\|<nowiki>nvidia-smi \| grep CUDA</nowiki>}}		{{code\|lang=console\|line=no\|<nowiki>nvidia-smi \| grep CUDA</nowiki>}}

	== <code>cudatoolkit</code>, <code>cudnn</code>, and related packages ==		== <code>cudatoolkit</code>, <code>cudnn</code>, and related packages ==

Smudgebun: Added a brief Driver Installation section, as it may be unclear to newer users whether or not they need to configure CUDA separately.

2026-04-11T07:20:44Z

Added a brief Driver Installation section, as it may be unclear to newer users whether or not they need to configure CUDA separately.

← Older revision		Revision as of 07:20, 11 April 2026
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	{{tip\|1='''Data center GPUs''': Note that you may need to adjust your driver version to use "data center" GPUs like V100/A100s. See [https://discourse.nixos.org/t/how-to-use-nvidia-v100-a100-gpus/17754 this thread] for more info.}}		{{tip\|1='''Data center GPUs''': Note that you may need to adjust your driver version to use "data center" GPUs like V100/A100s. See [https://discourse.nixos.org/t/how-to-use-nvidia-v100-a100-gpus/17754 this thread] for more info.}}

			== Driver Installation ==

			Assuming you've followed the [[NVIDIA]] page correctly, and have a CUDA compatible GPU, you shouldn't need to do any further configuration. You can confirm your CUDA version by running the following command in your terminal.

			{{code\|lang=sh\|line=no\|<nowiki>nvidia-smi \| grep CUDA</nowiki>}}

	== <code>cudatoolkit</code>, <code>cudnn</code>, and related packages ==		== <code>cudatoolkit</code>, <code>cudnn</code>, and related packages ==

Smudgebun: /* Setting up CUDA Binary Cache */ Changed the Warning template to an Info template, as I think it fits the use case as described in the MoS better.

2026-04-11T06:47:17Z

Setting up CUDA Binary Cache: Changed the Warning template to an Info template, as I think it fits the use case as described in the MoS better.

← Older revision		Revision as of 06:47, 11 April 2026
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	For more information, refer to the [[Binary Cache#Using a binary cache Using a binary cache\|Using a binary cache]] page.		For more information, refer to the [[Binary Cache#Using a binary cache Using a binary cache\|Using a binary cache]] page.

	{{~~warning~~\|1=You need to rebuild your system at least once after adding the cache, before it can be used.}}		{{info\|1=You need to rebuild your system at least once after adding the cache, before it can be used.}}

	=== NixOS ===		=== NixOS ===

Smudgebun: /* Enabling CUDA In Packages */ Improved the structure and clarity of the section

2026-04-11T06:44:22Z

Enabling CUDA In Packages: Improved the structure and clarity of the section

← Older revision		Revision as of 06:44, 11 April 2026
Line 198:		Line 198:
	Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.		Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.

	If you will be using <code>cudaSupport</code> in packages, it is highly recommended you utilize the [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]]. Without it, any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) packages with CUDA support enabled due to the license.		{{info\|If you will be using <code>cudaSupport</code> in packages, it is highly recommended you utilize the [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]].}}

	~~For larger programs like Blender that process can be very resource-intensive. If you know you are installing a large package and do not have~~ the ~~cache configured~~, ~~it is recommended to limit the number of cores and/or jobs that the process will take, to prevent a crash. This can be done~~ with ~~the~~ <code>~~--max-jobs</code> / <code>-j~~</code> and ~~<code>--cores</code> flags, for more details see:~~ [https://~~github~~.~~com~~/~~NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs~~.~~md Tuning Cores & Jobs~~].		Without the CUDA Cache, any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) CUDA packages.

	~~This is also why it is recommended~~, if you cannot use the cache, to ~~enable~~ <code>~~cudaSupport~~</code> ~~only~~ for the ~~programs you need it for, to avoid pointlessly compiling packages from~~ source.		For larger programs like Blender, that process can be very resource-intensive. If you know you are installing a large package and cannot use the cache, it is recommended to reduce the number of cores and/or jobs that the process will take, to prevent a crash from memory limits. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see the [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs] page.

	For specifics on setting up Blender with CUDA see: [[Blender#CUDA & OptiX]].		→ For specifics on setting up Blender with CUDA (and OptiX) see: [[Blender#CUDA & OptiX]].

	== Some things to keep in mind when setting up CUDA in NixOS ==		== Some things to keep in mind when setting up CUDA in NixOS ==

Smudgebun: /* Enabling CUDA In Packages */ Restructured the paragraphs to hopefully be more clear

2026-04-11T06:10:34Z

Enabling CUDA In Packages: Restructured the paragraphs to hopefully be more clear

← Older revision		Revision as of 06:10, 11 April 2026
Line 198:		Line 198:
	Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.		Or you can use binary-packaged versions of CUDA compatible software, such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin] for Blender.

	~~Without~~ the [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]], any CUDA-compatible package installed with ~~the~~ <code>cudaSupport</code> ~~flag enabled~~ will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) packages with CUDA support enabled due to the license. For larger programs like Blender this can be very resource-intensive. If you know you are building a large package and do not have the cache configured, it is recommended to limit the number of cores or jobs that the process will take, to prevent a crash. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see: [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs].		If you will be using <code>cudaSupport</code> in packages, it is highly recommended you utilize the [[#Setting up CUDA Binary Cache\|CUDA Binary Cache]]. Without it, any CUDA compatible package installed with <code>cudaSupport</code> will be compiled from source. This is because NixOS Foundation does not build (and therefore [https://cache.nixos.org/ cache.nixos.org] does not cache) packages with CUDA support enabled due to the license.

	This is also why it is recommended, if ~~without~~ the cache, to enable <code>cudaSupport</code> only for the programs you need it for, to avoid pointlessly compiling packages from source.		For larger programs like Blender that process can be very resource-intensive. If you know you are installing a large package and do not have the cache configured, it is recommended to limit the number of cores and/or jobs that the process will take, to prevent a crash. This can be done with the <code>--max-jobs</code> / <code>-j</code> and <code>--cores</code> flags, for more details see: [https://github.com/NixOS/nix/blob/master/doc/manual/source/advanced-topics/cores-vs-jobs.md Tuning Cores & Jobs].

			This is also why it is recommended, if you cannot use the cache, to enable <code>cudaSupport</code> only for the programs you need it for, to avoid pointlessly compiling packages from source.

	For specifics on setting up Blender with CUDA see: [[Blender#CUDA & OptiX]].		For specifics on setting up Blender with CUDA see: [[Blender#CUDA & OptiX]].

Smudgebun: Expanded a new `Enabling CUDA In Packages` section because the information was left as effectively a footnote previously.

2026-04-11T02:17:17Z

Expanded a new `Enabling CUDA In Packages` section because the information was left as effectively a footnote previously.

@@ Line 180: / Line 180: @@
 trusted-substituters = https://cache.nixos-cuda.org
 </nowiki>|name=~/.config/nix/nix.conf|lang=nix}}
 == Some things to keep in mind when setting up CUDA in NixOS ==
 * Some GPUs, like Tesla K80, don't work with the latest drivers, so you must specify them in the option <code>hardware.nvidia.package</code> getting the value from your selected kernel, for example, <code>config.boot.kernelPackages.nvidia_x11_legacy470</code>. You can check which driver version your GPU supports by visiting the  [https://www.nvidia.com/Download/index.aspx nvidia site] and checking the driver version.
 * Even with the drivers correctly installed, some software, like Blender, may not see the CUDA GPU. Make sure your system configuration has the option <code>hardware.graphics.enable</code> enabled.
 == CUDA under WSL ==

Smudgebun: /* Some things to keep in mind when setting up CUDA in NixOS */ Added in-line code examples and a link to the Blender page's CUDA section.

2026-04-10T23:48:53Z

Some things to keep in mind when setting up CUDA in NixOS: Added in-line code examples and a link to the Blender page's CUDA section.

← Older revision		Revision as of 23:48, 10 April 2026
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	* Some GPUs, like Tesla K80, don't work with the latest drivers, so you must specify them in the option <code>hardware.nvidia.package</code> getting the value from your selected kernel, for example, <code>config.boot.kernelPackages.nvidia_x11_legacy470</code>. You can check which driver version your GPU supports by visiting the [https://www.nvidia.com/Download/index.aspx nvidia site] and checking the driver version.		* Some GPUs, like Tesla K80, don't work with the latest drivers, so you must specify them in the option <code>hardware.nvidia.package</code> getting the value from your selected kernel, for example, <code>config.boot.kernelPackages.nvidia_x11_legacy470</code>. You can check which driver version your GPU supports by visiting the [https://www.nvidia.com/Download/index.aspx nvidia site] and checking the driver version.
	* Even with the drivers correctly installed, some software, like Blender, may not see the CUDA GPU. Make sure your system configuration has the option <code>hardware.graphics.enable</code> enabled.		* Even with the drivers correctly installed, some software, like Blender, may not see the CUDA GPU. Make sure your system configuration has the option <code>hardware.graphics.enable</code> enabled.
	* By default, software packaged in source code form has CUDA support disabled, because of the unfree license. To solve this, you can enable builds with CUDA support with a nixpkgs wide configuration, or use binary packaged CUDA compatible software such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin].		* By default, software packaged in source code form has CUDA support disabled, because of the unfree license. To solve this, you can enable builds with CUDA support with a nixpkgs wide configuration <code>nixpkgs.config.cudaSupport = true;</code>, individual overrides e.g. <code>environment.systemPackages = with pkgs; [ (blender.override {config.cudaSupport=true;}) ];</code>, or use binary packaged CUDA compatible software such as [https://github.com/edolstra/nix-warez/tree/master/blender blender-bin].
			* For setting up Blender with CUDA see: [[Blender#CUDA & OptiX]].

	== CUDA under WSL ==		== CUDA under WSL ==