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GPU-accelerated video analysis — index your library faster

Indexing hundreds of clips — thumbnails, detected content, transcripts, face data — takes time. ClipCatalog offloads the heavy lifting to your GPU so your library becomes searchable faster, and falls back to CPU automatically when GPU isn't available. Available on Windows 10 and 11.

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ClipCatalog GPU acceleration settings on Windows and processing queue.

Faster first-time indexing

GPU acceleration cuts initial processing time — especially when generating detected content, transcripts, and face data simultaneously. Get to "searchable" faster.

Graceful CPU fallback

No dedicated GPU? No problem. ClipCatalog detects your hardware and falls back to CPU automatically — no crashes, no configuration, no lost work.

Stop & resume anytime

Processing is built for large libraries. Pause and resume indexing at any time without losing progress — ideal for terabyte-scale archives.

How GPU acceleration works in ClipCatalog

ClipCatalog uses two GPU backends for different tasks — each one designed to work across GPU brands on Windows, with automatic fallback to CPU when needed.

1
DirectML — content detection

Detected content (RAM++ model) runs via DirectML — a low-level Windows API that works across NVIDIA, AMD, and Intel GPUs with DirectX 12 support.

2
Vulkan — transcription

Speech-to-text transcription (whisper.cpp) uses Vulkan for GPU acceleration. Vulkan is a cross-vendor standard supported by most modern GPUs.

3
OpenCL — face detection

The optional face detection pipeline (YuNet + SFace) supports OpenCL acceleration when available, speeding up face analysis on compatible systems.

Built-in benchmark — find the fastest backend for your hardware

Not sure if GPU acceleration helps on your setup? ClipCatalog includes a one-click transcription benchmark that tests CPU and GPU on the same audio sample, reports the speed of each, and auto-selects the winner.

One-click, under a minute

The benchmark runs a short transcription sample on both CPU and GPU, measures processing speed for each, and picks the winner. It takes under a minute and the result is cached permanently — you only need to run it once.

Three transcription modes

Choose between Auto (uses benchmark result + heuristics), CPU-only, or GPU (Vulkan). Auto mode is the default and makes the right call for most systems — including detecting iGPU-only setups where CPU may actually be faster.

ClipCatalog built-in transcription benchmark showing GPU vs CPU speed results on an Intel Arc GPU
The built-in benchmark compares GPU and CPU transcription speed on your hardware.

Choose which GPU to use

If your system has more than one GPU — a common setup with a dedicated card plus an integrated one — ClipCatalog lets you pick which GPU to use directly in Settings.

Vendor badges

See NVIDIA, AMD, or Intel at a glance

VRAM display

Know your GPU's memory before you start

iGPU indicator

Clearly marked integrated GPUs

Persisted selection

Your GPU preference survives reboots

ClipCatalog GPU selection dropdown showing NVIDIA, AMD, and Intel GPUs with VRAM and vendor badges
The GPU selection dropdown in ClipCatalog Settings.

When GPU acceleration makes the biggest difference

First-time library indexing

The initial processing pass — generating tags, transcripts, and face data for every clip — is the most GPU-intensive step. After your library is indexed, search is instant regardless of GPU. Think of it as a one-time investment.

Large shoot days

Import a full day's footage and let GPU acceleration crunch through it while you work on something else. For YouTubers and vloggers, this means searchable footage by the time you're ready to edit.

Terabyte-scale archives

Filmmakers and editors with years of accumulated footage can process their archive in stages. Combined with stop-and-resume, GPU acceleration makes indexing large libraries practical instead of overnight.

Multi-feature processing

When you enable detected content, transcripts, and face recognition together, each pipeline stage benefits from GPU acceleration — so the total time savings compound.

What to expect

Same results, faster

GPU acceleration doesn't change the quality of tags, transcripts, or face detection. The AI models produce identical results whether they run on GPU or CPU — the only difference is how fast they finish.

100% local — no cloud processing

GPU acceleration means your own graphics card does the work — right on your desk. Your footage is never uploaded to a cloud service. Learn about local-first privacy →

Resilient to GPU issues

If your GPU runs out of memory, hits a driver error, or isn't compatible, ClipCatalog falls back to CPU for that task and keeps processing. No crash, no lost progress, no manual intervention.

Works with external drives

GPU acceleration works regardless of where your footage lives — internal drives, external SSDs, or archive volumes. Learn about external drive support →

Hardware compatibility

ClipCatalog's GPU acceleration is designed to work across hardware — no vendor lock-in.

GPU backend and hardware requirements by feature
Feature GPU backend Requirement
Detected content (RAM++) DirectML DirectX 12 compatible GPU
Transcription (whisper.cpp) Vulkan Vulkan-capable GPU + drivers
Face detection (YuNet + SFace) OpenCL OpenCL-capable GPU (optional)
All features — CPU fallback None Any Windows 10/11 PC

Most GPUs from the last several years support all three backends. If your drivers are outdated or incompatible, ClipCatalog falls back to CPU without crashing.

Frequently asked questions

Do I need a dedicated GPU to use ClipCatalog?

No. GPU acceleration is optional. ClipCatalog detects your hardware and falls back to CPU when a capable GPU isn’t available. Everything works — processing just takes a bit longer on CPU.

Which GPUs are supported?

Detected content uses DirectML, which works across NVIDIA, AMD, and Intel GPUs on Windows with DirectX 12 support. Transcription uses Vulkan, which is supported by most modern GPUs. You don’t need a specific brand.

Does GPU acceleration change the quality of tags or transcripts?

No. The AI models produce the same results whether they run on GPU or CPU. The difference is purely speed.

How much faster is GPU vs. CPU?

It depends on your hardware. ClipCatalog includes a built-in benchmark that tests both backends on your specific system. Dedicated GPUs typically process significantly faster — but the benchmark gives you a concrete answer for your setup.

Will GPU acceleration upload my footage to the cloud?

No. All processing runs locally on your machine. GPU acceleration means your own graphics card does the work — nothing is uploaded anywhere.

What happens if my GPU runs out of memory during processing?

ClipCatalog falls back to CPU automatically. There’s no crash and no lost progress — it logs the fallback and keeps going.

Can I choose which GPU to use if I have more than one?

Yes. The Settings screen shows a GPU dropdown with vendor badges (NVIDIA, AMD, Intel), VRAM, and whether it’s an integrated GPU. Your selection persists across reboots.

Does it work with integrated GPUs (iGPU)?

Integrated GPUs can provide some acceleration, but dedicated GPUs are faster. ClipCatalog’s auto mode uses benchmark results plus heuristics to pick the best option for your system.

Best for

Try the benchmark yourself

The best way to see if GPU acceleration helps on your setup: install ClipCatalog, open Settings, and run the built-in transcription benchmark. After a few minutes you have concrete results.

Free trial — up to 500 videos, no credit card
GPU acceleration included in the trial
Windows only — download here or see pricing

Understanding GPU-accelerated video analysis

Whether you're evaluating GPU requirements, comparing backends, or wondering if your hardware is fast enough — here's what matters for local video indexing with AI.

Why GPU matters for video indexing

AI models like RAM++ (content detection) and whisper.cpp (transcription) perform thousands of parallel matrix operations per frame or audio chunk. GPUs are built for exactly this kind of work — thousands of cores processing in parallel — which is why they can be significantly faster than CPUs for these tasks.

DirectML vs. CUDA — no vendor lock-in

Many GPU-accelerated tools require NVIDIA CUDA, locking out AMD and Intel users. ClipCatalog uses DirectML and Vulkan instead — cross-vendor standards that work with any modern GPU on Windows. You don't need to install CUDA, cuDNN, or vendor-specific SDKs.

Integrated GPU vs. dedicated

Integrated GPUs (like Intel Iris or AMD Radeon integrated) share system memory and have fewer cores than dedicated cards. They can still provide some acceleration, but dedicated GPUs will always be faster. ClipCatalog's auto mode detects iGPU-only systems and adjusts its recommendation accordingly.

Driver compatibility

GPU acceleration depends on up-to-date drivers. If your drivers are outdated or the GPU doesn't support the required API version, ClipCatalog doesn't crash — it logs the issue and continues on CPU. You can check your GPU status in Settings at any time.

Try ClipCatalog free — up to 500 videos

No account required. Your footage stays on your computer.

500 videos free 14-day refund One-time purchase