Before choosing a graphics card for AI video, decide what you need the project to do: which models and tools you will use, whether you need guided frames and upscaling, whether generation will run locally or through a hosted service, and whether the finished work must be commercially usable. Those choices determine which hardware requirements and terms actually apply. A 16 GB VRAM figure is a requirement for one documented NVIDIA workflow—not a universal minimum for AI video.
What should you decide before buying hardware?
Write down the intended workflow and output before comparing GPUs. A prompt-to-video experiment, a carefully staged local pipeline, and a hosted service have different software, hardware, and terms. The useful question is not simply “How much VRAM do I need to run video generation locally?” but “How much memory does this chosen model and workflow require at the resolution and stages I plan to use?”
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- Choose the models and software. Confirm their current system requirements and licenses; requirements for one stack do not establish requirements for another.
- Choose the level of control. Decide whether a text prompt is enough or whether you need scene layout, guided images, video generation, and an upscale stage.
- Choose local or hosted generation. Local generation makes your computer’s components and setup central. Hosted generation shifts much of that workload to a provider but makes its agreement, account terms, and data handling relevant.
- Define the intended use. Commercial permission, rights to source material, and any disclosure obligations need checking for the project—not inferred from a model’s name or a service’s general marketing.
Do not extrapolate a general performance or cost estimate from a single vendor’s requirements. The available figures below describe one specific setup.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsWhat does NVIDIA’s local workflow require?
NVIDIA’s Video Generation Guide, published March 17, 2026, documents a Windows 11 workflow using Blender, ComfyUI, FLUX.1, LTX-2.3, and RTX Video Super Resolution. For that workflow, NVIDIA specifies 64 GB of system RAM and a GPU with 16 GB of VRAM, and recommends a GeForce RTX 5070 Ti or higher. These are NVIDIA’s figures for its documented pipeline, not an industry-wide minimum or a guarantee that another model, resolution, or software combination will work the same way. Read NVIDIA’s guide.
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| Item | NVIDIA’s stated figure or choice | Scope |
|---|---|---|
| Operating system | Windows 11 | NVIDIA’s documented workflow |
| System RAM | 64 GB | NVIDIA’s stated requirement for that workflow |
| GPU memory | 16 GB VRAM | NVIDIA’s stated GPU requirement for that workflow |
| GPU recommendation | GeForce RTX 5070 Ti or higher | NVIDIA’s recommendation for that workflow |
If your plan uses a different local model or hosted generation, check the applicable requirements directly rather than treating this table as a baseline for every option. The guide also recommends completing stages in sequence when using its full pipeline so system resources are available for the next step.
Why use a staged workflow instead of only a prompt?
NVIDIA’s guide describes a pipeline that begins with text-described 3D objects, uses Blender to establish composition, creates guided first and last frames, generates video with LTX-2.3, and then upscales through an RTX Video Super Resolution node in ComfyUI. NVIDIA author Joel Pennington notes that “Generating AI video with just a text prompt gives you limited control over the results.” The staged approach gives the creator more places to shape composition before video generation; it also means more software and processing stages to plan for.
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- Build a scene. Use Blender to arrange the 3D elements and composition that will guide the images.
- Create guided frames. Produce the first and last images that will anchor the video-generation stage.
- Generate the video. Pass those images into LTX-2.3 as described in NVIDIA’s workflow.
- Upscale if needed. Use the guide’s RTX Video Super Resolution node in ComfyUI for the final processing stage.
NVIDIA says users can select individual blueprint pieces rather than adopt the entire pipeline. The complete staged process may be useful when composition control matters; a simpler approach may be more suitable when those controls or the upscale stage are unnecessary.
Can you use the result commercially?
Check permissions at the level of each model, component, service, and input. A commercial-use statement for one service does not grant rights to content you do not own, and a license for a model does not automatically settle the terms of bundled components or later uses of its output.
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NVIDIA’s documented FLUX.1 step
NVIDIA labels the FLUX.1-based “3D Guided Generative AI” blueprint in its guide as non-commercial and directs users to Black Forest Labs for commercial use. That warning applies to this particular step; it is not a blanket conclusion about every asset or model in the pipeline. Check the terms for each component you plan to use.
NVIDIA model licenses
The NVIDIA Community Model License, last modified January 30, 2025, describes limited grants and conditions on distribution and production use. For some models, production use requires NVIDIA NIM through an NVIDIA AI Enterprise subscription. The license states exceptions for designated RTX or GeForce RTX use on a PC or workstation that is not a multi-user commercial kiosk or server, and for specified models used locally and integrated into an application. It also places responsibility on users to have sufficient rights or licenses for content used with the models. Check the exact model designation and current agreement: NVIDIA Community Model License.
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NVIDIA’s Open Model License Agreement, last modified October 24, 2025, grants specified worldwide, royalty-free rights subject to its conditions. It says NVIDIA claims no ownership of outputs, but redistribution of the model requires a copy of the agreement and an attribution notice; bundled components may carry separate notices and terms. Review the actual agreement rather than treating the license title as a summary of every component’s rights: NVIDIA Open Model License Agreement.
Hosted service terms and data handling
Runway’s Help Center says users may use its generations commercially without non-commercial restrictions from Runway, subject to its applicable agreement and Usage Policy. It also states: “As between you and Runway, you retain ownership and all your rights to content you upload and generate on Runway.” That statement describes the relationship between the user and Runway; it does not clear rights in a likeness, trademark, or third-party input. Review the Runway usage-rights FAQ and the agreement and policy that apply to your account.
Commercial permission and data terms are separate questions. Runway’s developer guidance says its Enterprise agreement includes contractual no-training and zero-retention provisions. Confirm whether those terms apply to your account and project before uploading sensitive material; do not assume commercial-use permission answers how inputs are handled. Runway’s developer guidance also discusses disclosure considerations, which can depend on context and applicable rules.
Quick Recap
Use this checklist before committing to a setup
- List the models, software, output resolution, and processing stages you intend to use.
- Decide whether the project needs local control and staged composition, or whether a hosted workflow meets the need.
- For local generation, verify the chosen models’ requirements for GPU VRAM and system RAM; use NVIDIA’s figures only if adopting its documented workflow.
- For every model and component, check the current license, commercial-use terms, and any redistribution conditions.
- Confirm that you have rights to the inputs, and separately check the service’s data-retention, training, and disclosure terms where relevant.
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