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Speed up encoding by 5-10x using your computer’s graphics card (GPU) instead of just the CPU.
What is GPU acceleration? Using your graphics card to encode videos much faster than CPU-only encoding. See hardware acceleration in the glossary.
Performance boost: A movie that takes 2 hours to encode on CPU finishes in 15-20 minutes with GPU hardware acceleration.

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Supported Hardware

NVIDIA

NVENC (Best Quality)
  • GTX 1050+
  • RTX 20/30/40 series
  • Requires NVIDIA drivers 450+
Performance: 5-10x faster

Intel

Quick Sync (QSV)
  • 6th gen (Skylake)+
  • Built into CPU (no separate GPU needed)
  • Arc GPUs support AV1
Performance: 3-8x faster

AMD

VCE/VCN
  • RX 400/500/5000/6000/7000 series
  • Limited support
Performance: 3-6x faster
Quality trade-off: Hardware acceleration encodes slightly faster than CPU at the cost of minor quality reduction. For most content, this is imperceptible. See codec selection for quality comparisons.

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Checking Hardware Support

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NVIDIA GPUs

Check if your NVIDIA GPU is detected: 
# Check GPU is recognized
nvidia-smi

# Should show:
# +-----------------------------------------------------------------------------+
# | NVIDIA-SMI 525.60.11    Driver Version: 525.60.11    CUDA Version: 12.0     |
# |-------------------------------+----------------------+----------------------+
# | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
# | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
# |                               |                      |               MIG M. |
# |===============================+======================+======================|
# |   0  NVIDIA GeForce ...  Off  | 00000000:01:00.0 Off |                  N/A |
If nvidia-smi shows your GPU, you’re ready to enable hardware acceleration.

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Intel Quick Sync

Check if Intel QSV is available: 
# Check for Intel GPU device
ls -la /dev/dri

# Should show:
# drwxr-xr-x  3 root root        100 Jan 10 12:00 .
# crw-rw----  1 root video  226,   0 Jan 10 12:00 card0
# crw-rw----  1 root video  226, 128 Jan 10 12:00 renderD128
Intel iGPU: Built into your CPU. Even if you have a dedicated GPU, Intel Quick Sync can still be used for encoding.

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AMD GPUs

Check if AMD GPU is detected: 
# Check for AMD GPU device
ls -la /dev/dri

# Check AMD GPU info
rocm-smi

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Docker GPU Passthrough

To use hardware acceleration, you need to give Docker access to your GPU.

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NVIDIA Setup

1

Install NVIDIA Container Toolkit

# Detect your distribution
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)

# Add NVIDIA Docker repository
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
  sudo tee /etc/apt/sources.list.d/nvidia-docker.list

# Install toolkit
sudo apt update && sudo apt install -y nvidia-container-toolkit

# Restart Docker
sudo systemctl restart docker
2

Update docker-compose.yml

Add GPU passthrough to your docker-compose.yml:
services:
  bitbonsai-backend:
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
What this does: Gives the BitBonsai backend access to your NVIDIA GPU for hardware encoding.
3

Restart BitBonsai

cd /path/to/bitbonsai
docker compose down
docker compose up -d
4

Verify GPU is Accessible

# Check GPU is visible inside container
docker exec bitbonsai-backend nvidia-smi

# Should show GPU info
Unraid users: GPU passthrough is automatic if you enable NVIDIA support in Unraid settings.

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Intel Quick Sync Setup

1

Enable iGPU in BIOS

  • Enter BIOS/UEFI settings
  • Enable Integrated Graphics or iGPU
  • Set Primary Display to iGPU (if you have dedicated GPU)
  • Save and reboot
Why? Intel Quick Sync requires the iGPU to be enabled even if you have a dedicated GPU.
2

Verify /dev/dri Device

ls -la /dev/dri

# Should show:
# crw-rw---- 1 root video 226,   0 Jan 10 12:00 card0
# crw-rw---- 1 root video 226, 128 Jan 10 12:00 renderD128
If missing, install Intel drivers:
# Ubuntu/Debian
sudo apt install intel-media-va-driver-non-free

# Arch Linux
sudo pacman -S intel-media-driver
3

Update docker-compose.yml

Add device passthrough:
services:
  bitbonsai-backend:
    devices:
      - /dev/dri:/dev/dri
What this does: Gives BitBonsai access to Intel Quick Sync for hardware encoding.
4

Restart BitBonsai

docker compose down
docker compose up -d
Headless servers: If you don’t have a monitor connected, you may need a dummy HDMI plug to keep the iGPU active.

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AMD Setup

1

Install ROCm Drivers

# Ubuntu 22.04
wget https://repo.radeon.com/amdgpu-install/latest/ubuntu/jammy/amdgpu-install_*_all.deb
sudo apt install ./amdgpu-install_*_all.deb
sudo amdgpu-install --usecase=graphics,rocm
2

Update docker-compose.yml

Add device passthrough:
services:
  bitbonsai-backend:
    devices:
      - /dev/dri:/dev/dri
      - /dev/kfd:/dev/kfd
    group_add:
      - video
      - render
3

Restart BitBonsai

docker compose down
docker compose up -d
AMD quality: AMD hardware encoders have noticeably lower quality than NVIDIA/Intel. Use only if NVENC/QSV unavailable.

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Enable in BitBonsai

After configuring Docker GPU passthrough:
1

Open BitBonsai Settings

Navigate to Settings → Encoding in the web UI
2

Enable Hardware Acceleration

  • Toggle Hardware Acceleration: ON
  • Select your GPU type:
    • NVIDIA → NVENC
    • Intel → QSV (Quick Sync)
    • AMD → VCE/VCN
3

Select Codec

  • HEVC (H.265): Supported by all GPUs
  • AV1: Only Intel Arc GPUs (A380/A750/A770)
See codec selection for details.
4

Start Encoding

Queue videos and start encoding. You should see:
  • 5-10x faster speeds (NVIDIA)
  • 3-8x faster speeds (Intel)
  • 3-6x faster speeds (AMD)
Verify it’s working: Check the Encoding tab → active jobs should show 40-100 FPS (vs 5-15 FPS CPU-only).

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Performance Comparison

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1080p Movie (2 hours, 10 GB H.264 → HEVC)

HardwareSpeedTimeQuality
Intel i5-12400 (CPU)15 FPS75 minExcellent
NVIDIA RTX 3060 (GPU)80 FPS15 minNear-identical
Intel i5-12400 (QSV)45 FPS25 minVery good
AMD RX 6600 XT (VCE)35 FPS35 minGood
Best value: NVIDIA RTX 3060 provides excellent quality at 5x CPU speed for ~$300.

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4K Movie (2 hours, 50 GB H.264 → HEVC)

HardwareSpeedTimeQuality
Intel i9-13900K (CPU)5 FPS5 hoursExcellent
NVIDIA RTX 4090 (GPU)60 FPS40 minNear-identical
Intel i9-13900K (QSV)15 FPS2 hoursVery good

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Troubleshooting

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GPU Not Detected in Container

Symptom: BitBonsai shows “No GPU detected” in settings Fix: 
# Verify GPU is visible inside container
docker exec bitbonsai-backend nvidia-smi  # NVIDIA
docker exec bitbonsai-backend ls -la /dev/dri  # Intel/AMD

# If missing, check docker-compose.yml has correct device passthrough

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Encoding Still Slow After Enabling GPU

Possible causes:
  • Hardware acceleration not enabled in Settings → Encoding
  • Wrong GPU type selected (e.g., selected NVENC but have Intel QSV)
  • GPU is being used by another process (gaming, video editing)
Fix:
  1. Check Settings → Encoding → Hardware Acceleration is ON
  2. Verify correct GPU type is selected
  3. Close other GPU-intensive applications

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Poor Quality with Hardware Encoding

Symptom: Encoded videos have visible compression artifacts Fix:
  • Lower CRF value (Settings → Encoding → Quality)
    • Try CRF 18-20 instead of default 23
  • Switch to slower preset (NVIDIA: use p7 instead of p4)
  • For critical content, use CPU encoding instead