8mb.local – Self-Hosted GPU Video Compressor

8mb.local is a self-hosted, fire-and-forget video compressor. Drop a file, choose a target size (e.g., 8 MB, 25 MB, 50 MB, 100 MB), and let GPU-accelerated encoding produce compact outputs with AV1/HEVC/H.264. Supports NVIDIA NVENC hardware encoding with automatic CPU fallback. The stack includes a SvelteKit UI, FastAPI backend, Celery worker, Redis broker, and real-time progress via Server-Sent Events (SSE).

Video Demo

Features

NVIDIA NVENC hardware encoding with automatic CPU fallback when no GPU is available
Robust encoder validation at startup — tests actual encoder initialization, not just availability
AV1, HEVC (H.265), and H.264 encoding via NVENC or CPU software encoders
Drag-and-drop UI with helpful presets and advanced options (codec, container, tune, audio bitrate)
Configurable codec visibility — enable/disable specific codecs in the Settings page
Resolution control — set max width/height while maintaining aspect ratio
Video trimming — specify start/end times (seconds or HH:MM:SS format)
Real-time progress tracking using output size, time processed, bitrate, and wall-clock estimates
Real-time FFmpeg logs streamed during compression
Live queue management — view all active jobs with real-time progress, cancel individual jobs, or clear entire queue
Automatic file size optimization — re-encodes with adjusted bitrate if output exceeds target by >2%
Batch processing — compress multiple files in a single operation
Job history enabled by default
Auto-download enabled by default
Output container choice: MP4 or MKV, with compatibility safeguards
Version tracking — UI displays current version, backend provides /api/version

Screenshots

Main Interface	GPU Support List	Settings Panel
Live Queue	Compressing (Real-time Logs)	Encoder Validation Tests
Job History	Advanced Options

Architecture

flowchart LR
  A[Browser / SvelteKit UI] -- Upload / SSE --> B(FastAPI Backend)
  B -- Enqueue --> C[Redis]
  D[Celery Worker + FFmpeg NVENC] -- Progress / Logs --> C
  B -- Pub/Sub relay --> A
  D -- Files --> E[outputs/]
  A -- Download --> B

Components

Layer	Technology	Role
Frontend	SvelteKit + Vite	Drag-and-drop UI, size estimates, SSE progress/logs, download
Backend API	FastAPI	Accepts uploads, runs ffprobe, relays SSE, serves downloads
Worker	Celery + FFmpeg 6.1.1	Compression with NVENC or CPU; parses `ffmpeg -progress`
Broker	Redis	Celery broker and pub/sub transport for progress events

Data & files

uploads/ — incoming files (cleaned up after FILE_RETENTION_HOURS)
outputs/ — compressed results (cleaned up on the same schedule)

All components run in a single container via supervisord.

Installation

Quick Start (Docker Hub)

NVIDIA GPU

docker run -d \
  --name 8mblocal \
  --gpus all \
  -e NVIDIA_DRIVER_CAPABILITIES=compute,video,utility \
  -p 8001:8001 \
  -v ./uploads:/app/uploads \
  -v ./outputs:/app/outputs \
  jms1717/8mblocal:latest

The -e NVIDIA_DRIVER_CAPABILITIES=compute,video,utility flag is required — it tells the NVIDIA Container Toolkit to mount NVENC libraries into the container.

CPU Only (No GPU)

docker run -d \
  --name 8mblocal \
  -p 8001:8001 \
  -v ./uploads:/app/uploads \
  -v ./outputs:/app/outputs \
  jms1717/8mblocal:latest

Access the web UI at http://localhost:8001.

Docker Compose

NVIDIA GPU

services:
  8mblocal:
    image: jms1717/8mblocal:latest
    container_name: 8mblocal
    ports:
      - "8001:8001"
    volumes:
      - ./uploads:/app/uploads
      - ./outputs:/app/outputs
      - ./.env:/app/.env  # optional
    gpus: all
    environment:
      - NVIDIA_DRIVER_CAPABILITIES=compute,video,utility
    restart: unless-stopped

CPU Only

services:
  8mblocal:
    image: jms1717/8mblocal:latest
    container_name: 8mblocal
    ports:
      - "8001:8001"
    volumes:
      - ./uploads:/app/uploads
      - ./outputs:/app/outputs
      - ./.env:/app/.env  # optional
    restart: unless-stopped

Then run:

docker compose up -d

Building from Source

git clone https://github.com/JMS1717/8mb.local.git
cd 8mb.local
docker compose up -d --build

Platform Notes

Platform	GPU Support	Notes
Windows	NVIDIA via WSL2	Install Docker Desktop, enable WSL2 GPU support, install NVIDIA drivers
Linux	NVIDIA native	Install NVIDIA drivers + Container Toolkit
macOS	CPU only	Docker runs in a Linux VM without GPU passthrough

Verify Installation

# Check container status
docker ps | grep 8mblocal

# Check NVIDIA GPU access
docker exec 8mblocal nvidia-smi

# List available encoders
docker exec 8mblocal bash -c "ffmpeg -hide_banner -encoders | grep -E 'nvenc|264|265|av1'"

# View startup logs
docker logs 8mblocal

Update to Latest Version

docker compose pull
docker compose up -d

Or with docker run:

docker pull jms1717/8mblocal:latest
docker stop 8mblocal && docker rm 8mblocal
# Re-run your docker run command

Usage

Drop a video — drag and drop or click Choose File. Analysis runs automatically.
Pick a target size — click a preset button or enter a custom MB value.
Optional: open Advanced Options
- Video Codec: AV1 (best quality, RTX 40/50), HEVC (H.265), or H.264 (widest compatibility)
- Audio Codec: Opus (default) or AAC — MP4 containers auto-switch to AAC
- Speed/Quality: NVENC presets P1 (fastest) through P7 (best quality), default P6
- Container: MP4 (most compatible) or MKV (best with Opus audio)
- Tune: HQ (default), Low Latency, Ultra-Low Latency, or Lossless
- Resolution: Set max width/height to downscale while preserving aspect ratio
- Trimming: Set start/end times to compress only a portion
Click Compress and watch progress/logs in real time. Cancel anytime. Download starts automatically.

Tips

For very small targets, prefer AV1 or HEVC and keep audio around 96–128 kbps.
For speed, try Low Latency tune with a faster preset (P1–P4).
MP4 + Opus is not supported; the worker auto-switches to AAC for MP4 containers.
MP4 outputs include +faststart for better web/streaming playback.

Configuration

Environment Variables

Create a .env file and mount it at /app/.env:

# Authentication (also configurable via Settings UI)
AUTH_ENABLED=false
AUTH_USER=admin
AUTH_PASS=changeme

# File retention
FILE_RETENTION_HOURS=1

# Worker concurrency (max parallel jobs)
WORKER_CONCURRENCY=4

# Codec visibility (all default to true)
CODEC_H264_NVENC=true
CODEC_HEVC_NVENC=true
CODEC_AV1_NVENC=true
CODEC_LIBX264=true
CODEC_LIBX265=true
CODEC_LIBAOM_AV1=true

# Redis / backend (usually no need to change)
REDIS_URL=redis://127.0.0.1:6379/0
BACKEND_HOST=0.0.0.0
BACKEND_PORT=8001

Settings UI

Manage settings at /settings with no container restart required:

Authentication — enable/disable, manage credentials
Default Presets — target size, codec, quality, container defaults
Codec Visibility — enable/disable NVIDIA and CPU codecs
Preset Profiles — create named presets for quick access
Worker Concurrency — adjust parallel job limit
Size Buttons — customize the target size quick-pick buttons
GPU Support Reference — hardware encoding compatibility at /gpu-support

Performance & Concurrency

8mb.local supports multiple parallel compression jobs. Configure via Settings UI or WORKER_CONCURRENCY env var.

GPU	Recommended Concurrency	Notes
RTX 5090 / 5080 / 5070 Ti	8–12 jobs	9th gen NVENC (x2), top tier
RTX 4090 / 4080 / 4070 Ti	8–12 jobs	8th gen NVENC, excellent throughput
RTX 3090 / 3080 / 3070	6–10 jobs	7th gen NVENC (no AV1)
RTX 2080 Ti / 2070 / 2060	3–5 jobs	6th gen NVENC
GTX 1660 / 1650	2–4 jobs	Entry-level NVENC
CPU only	1–2 per 4 cores	High CPU usage, much slower

Considerations

Most consumer NVIDIA GPUs support 2–3 native NVENC sessions; driver patches or Pro GPUs allow more.
Each job uses ~200–500 MB RAM and ~100–200 MB VRAM.
SSD recommended for 6+ concurrent jobs (disk I/O becomes a bottleneck).
Monitor GPU temps — sustained load above 80 °C may cause throttling.
Start with 4 concurrent jobs and increase while monitoring utilization.

Container restart required after changing worker concurrency.

Reverse Proxy Configuration

SSE (Server-Sent Events) requires special proxy configuration to prevent buffering.

Nginx / Nginx Proxy Manager

location /api/stream/ {
    proxy_pass http://backend:8001;
    proxy_buffering off;
    proxy_cache off;
    proxy_set_header Connection '';
    chunked_transfer_encoding on;
}

In Nginx Proxy Manager: Edit Proxy Host → Advanced tab → Custom Nginx Configuration.

Traefik

labels:
  - "traefik.http.middlewares.no-buffer.buffering.maxRequestBodyBytes=0"
  - "traefik.http.middlewares.no-buffer.buffering.maxResponseBodyBytes=0"
  - "traefik.http.routers.8mblocal.middlewares=no-buffer"

Apache

<Location /api/stream/>
    ProxyPass http://backend:8001/api/stream/
    ProxyPassReverse http://backend:8001/api/stream/
    SetEnv proxy-sendchunked 1
    SetEnv proxy-interim-response RFC
</Location>

Why this matters: Without proxy_buffering off, your proxy buffers the entire SSE stream and delivers all progress events at once when the job completes — progress appears stuck at 0% until done.

Troubleshooting

Container won't start with `--gpus all`

If the host has no NVIDIA GPU, Docker's NVIDIA runtime hook will abort:

nvidia-container-cli: initialization error: WSL environment detected but no adapters were found

Fix: Remove --gpus all and any NVIDIA_* environment variables. The app will start in CPU mode automatically.

NVENC not working

1. Missing NVIDIA_DRIVER_CAPABILITIES

Symptom: Cannot load libnvidia-encode.so.1

Fix: Add the environment variable to your docker run or compose:

-e NVIDIA_DRIVER_CAPABILITIES=compute,video,utility

This tells the Container Toolkit to mount NVENC libraries into the container.

2. Driver too old (NVENC API mismatch)

Symptom: Driver does not support the required nvenc API version. Required: 13.0 Found: 12.1

This means your NVIDIA driver is 535.x or older. You need driver 550+.

# Debian 12
wget https://developer.download.nvidia.com/compute/cuda/repos/debian12/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt update && sudo apt install nvidia-driver
sudo reboot

# Ubuntu
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update && sudo apt install nvidia-driver-550
sudo reboot

Verify after reboot: nvidia-smi should show driver 550+.

3. Missing NVIDIA Container Toolkit

# Install (Debian/Ubuntu)
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
  | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
distribution=$(. /etc/os-release; echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list \
  | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
  | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker

If you can't upgrade the driver, the system will automatically fall back to CPU encoding. Your videos will still compress — just slower.

Progress bar stuck at 0%

Cause: Reverse proxy buffering SSE responses.

Fix: Add proxy_buffering off; for the /api/stream/ location. See Reverse Proxy Configuration.

File slightly over target size

This is handled automatically. If the output exceeds the target by more than 2%, the system re-encodes with a reduced bitrate (up to 2 retries). You'll see a notification and hear an audio alert.

General issues

Problem	Solution
Permission denied on uploads/outputs	`chmod 777 uploads outputs` or `chown $USER:$USER uploads outputs`
Port already in use	Change mapping: `-p 8080:8001`
Container won't start	`docker logs 8mblocal` to check errors; `docker rm -f 8mblocal` and retry
FFmpeg errors	Check logs in the UI; try CPU-only codecs (libx264/libx265/libaom-av1)

Quick Diagnostic Commands

docker ps | grep 8mblocal              # Is it running?
docker logs 8mblocal                   # Startup and runtime logs
docker exec 8mblocal nvidia-smi        # GPU visible?
docker exec 8mblocal ffmpeg -hide_banner -encoders 2>&1 | grep nvenc  # NVENC available?
docker restart 8mblocal                # Restart
docker logs -f 8mblocal               # Live log tail

License

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

You are free to use, share, and adapt this project for non-commercial purposes with appropriate attribution. Commercial use requires a separate license — please contact me directly.

Contributing

Pull requests welcome! Please ensure Docker builds succeed and test with your GPU hardware.

Support

For issues, questions, or feature requests, please open an issue on GitHub.

Name		Name	Last commit message	Last commit date
Latest commit History 191 Commits
.github		.github
backend-api/app		backend-api/app
docs		docs
frontend		frontend
outputs		outputs
uploads		uploads
worker		worker
.dockerignore		.dockerignore
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
docker-compose.gpu.yml		docker-compose.gpu.yml
docker-compose.yml		docker-compose.yml
entrypoint.sh		entrypoint.sh
host-vid.mp4		host-vid.mp4
requirements.txt		requirements.txt
supervisord.conf		supervisord.conf
test.mp4		test.mp4

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8mb.local – Self-Hosted GPU Video Compressor

Table of Contents

Features

Screenshots

Architecture

Installation

Quick Start (Docker Hub)

NVIDIA GPU

CPU Only (No GPU)

Docker Compose

NVIDIA GPU

CPU Only

Building from Source

Platform Notes

Verify Installation

Update to Latest Version

Usage

Configuration

Environment Variables

Settings UI

Performance & Concurrency

Reverse Proxy Configuration

Nginx / Nginx Proxy Manager

Traefik

Apache

Troubleshooting

Container won't start with --gpus all

NVENC not working

Progress bar stuck at 0%

File slightly over target size

General issues

Quick Diagnostic Commands

License

Contributing

Support

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