Session 3 of 3

Open Source Models & Cost Optimization

Break free from subscriptions. Learn to run powerful AI video models for free using open source alternatives and cloud computing.

⏱️ 1 Hour 💰 Zero Monthly Costs 🔓 Full Control

💡 Why Open Source?

💰

Cost Savings

HeyGen: $29/mo = $348/year
Runway: $12/mo = $144/year
Open Source: $0 (or pay-as-you-go cloud)

🔓

No Limitations

No monthly credit limits, no watermarks, no ToS restrictions. Generate unlimited videos on your own hardware.

🎨

Full Customization

Fine-tune models on your own data, modify code, create unique styles commercial tools don't offer.

🌍

Community Driven

Access cutting-edge research immediately, not months later. Community constantly improves models.

⚡ Reality Check: Open source isn't "easier" than commercial tools - it requires technical setup. But for serious creators producing >10 videos/month, the savings and freedom are worth it.

⚠️ The Technical Reality

Let's be honest about what open source requires:

Aspect Commercial (HeyGen/Sora) Open Source
Setup Time 5 minutes ✅ 1-3 hours first time
Technical Skills None needed ✅ Basic command line
Hardware Needed Any computer ✅ GPU with 12GB+ VRAM or cloud
Monthly Cost $30-100/month $0 (own GPU) or ~$10/month (cloud) ✅
Quality Excellent ✅ Comparable (sometimes better)
Support Official customer service ✅ Community forums
💡 Honest Recommendation: If you're making <5 videos/month, stick with commercial tools. If you're making 10+ videos/month or want a sustainable long-term solution, invest the time to learn open source.

🏆 Top Open Source Video Models

These are the best free models that rival commercial quality.

Best Overall

HunyuanVideo (Tencent)

Size: 13B parameters Quality: ⭐⭐⭐⭐⭐ Hardware: 48GB+ VRAM

Capabilities: Text-to-video, image-to-video, ultra-realistic textures, best open source quality

Best For: High-quality final videos, professional projects

Notable Fine-Tune: SkyReels V1 (specialized for human characters - PERFECT for your use case!)

Most Accessible

Mochi 1 (Genmo)

Size: 10B parameters Quality: ⭐⭐⭐⭐ Hardware: 24GB+ VRAM (single GPU)

Capabilities: 5.4 seconds at 30fps, strong prompt adherence, good motion quality

Best For: Quick iterations, testing concepts, accessible hardware

License: Apache 2.0 (fully commercial-friendly)

Budget Hardware

LTXVideo (Lightricks)

Size: Optimized for speed Quality: ⭐⭐⭐⭐ Hardware: 12GB VRAM minimum

Capabilities: 24fps at 768x512, blazing fast, runs on consumer GPUs

Best For: Rapid prototyping, users with limited hardware, high volume

Formats: Text-to-video, image-to-video, video-to-video

Longest Duration

Wan-2.1 (WaveSpeed / Alibaba)

Size: Multiple variants Quality: ⭐⭐⭐⭐ Hardware: 8GB VRAM (small model)

Capabilities: Extremely efficient, excellent image-to-video, smooth transitions

Best For: Users with limited hardware, budget-conscious creators

Models: T2V-1.3B (text), i2v-480p, i2v-720p

Open Sora Clone

Open-Sora 2.0 (HPC-AI Tech)

Size: 11B parameters Quality: ⭐⭐⭐⭐ Hardware: 40GB+ VRAM

Capabilities: 256px and 768px resolution, unified text-to-video and image-to-video

Best For: Academic research, experimenting with Sora-like architecture

Integration: Works with Flux for better quality

🖥️ Three Ways to Run Open Source Models

Choose your path based on budget and technical comfort.

1

Run on Your Own Hardware

Best for: Long-term creators

Buy or build a PC with a powerful GPU. Highest upfront cost, lowest ongoing cost.

Hardware Requirements

🥉 Entry Level (LTXVideo, Wan 2.1)

  • GPU: RTX 3060 (12GB VRAM) - ~$300 used
  • RAM: 16GB system RAM
  • Storage: 256GB SSD
  • Total Cost: $600-800

🥇 Pro Level (HunyuanVideo, all models)

  • GPU: RTX 4090 (24GB) x2 or A6000 (48GB) - $3000+
  • RAM: 64GB+ system RAM
  • Storage: 1TB NVMe SSD
  • Total Cost: $5000-8000

ROI Calculation

Commercial Tools Cost: $50/month (HeyGen + Runway) = $600/year

Mid-Range GPU Setup: $2500 one-time

Break-even: ~4 years

BUT: No monthly limits, can process unlimited videos, resell value remains

💡 UK Buying Tip: Check Scan.co.uk, Overclockers UK, or eBay for used professional GPUs (Quadro RTX, Tesla). Often cheaper than gaming cards with same VRAM.
2

Rent Cloud GPUs (Recommended for Beginners)

Best for: Testing & occasional use

Pay only for GPU time you use. No hardware investment required. Perfect for learning open source.

Vast.ai

Pricing: $0.20-0.80/hour (marketplace pricing)

Pros: Cheapest option, many GPU choices

Cons: Reliability varies, need to find good hosts

Best For: Budget-conscious users

Visit Vast.ai

Lambda Labs

Pricing: $1.10/hour (A100), $1.80/hour (H100)

Pros: Reliable, fast GPUs, good for heavy models

Cons: More expensive, sometimes fully booked

Best For: Professional projects, HunyuanVideo

Visit Lambda Labs

Google Colab Pro+

Pricing: $50/month unlimited

Pros: Familiar notebook interface, no setup

Cons: Session limits, slower GPUs

Best For: Python users, experimentation

Visit Colab

Cost Example: Making 5 Videos/Month

Per video: 4 scenes @ 2 minutes generation each = 8 min GPU time

5 videos: 40 minutes GPU time @ $0.50/hour = $0.33 per video

Monthly cost: ~$1.65 for GPU time

vs HeyGen: $29/month

Savings: $327/year

3

Use Platform Aggregators

Best for: Hybrid approach

Middle ground: Pre-configured platforms that run open source models for you. Easier than cloud rental, cheaper than commercial tools.

Replicate.com

  • Run any open source model via API
  • Pay per generation ($0.01-0.50 per video)
  • No GPU needed

Cost: ~$5-15/month for 10-30 videos

Visit Replicate

Modal.com

  • Serverless GPU deployment
  • $30/month free credit
  • Scale up/down as needed

Cost: Free tier covers light usage

Visit Modal

Fal.ai

  • Optimized inference for video models
  • Fast generation times
  • Simple API

Cost: Pay per use, ~$0.10-0.40 per video

Visit Fal.ai

🎓 Beginner Tutorial: Run Mochi 1 on RunPod

Let's run your first open source model together. We'll use Mochi 1 (accessible) on RunPod (beginner-friendly).

1

Setup RunPod Account

⏱️ 10 minutes
  1. Go to runpod.io
  2. Click "Get Started" → Create account
  3. Add $10 credit (enough for 20+ hours of testing)
  4. Navigate to "GPU Instances"
2

Deploy Mochi 1 Container

⏱️ 5 minutes
  1. Click "Deploy" button
  2. Select GPU: RTX 4090 or RTX A6000
  3. In "Template" dropdown, search "ComfyUI" or "Text-to-Video"
  4. If available, select a Mochi 1 template (community-created)
  5. If not, select "PyTorch" template - we'll install Mochi manually
  6. Click "Continue" → "Deploy On-Demand"
  7. Wait 2-5 minutes for instance to start
💳 Cost Alert: GPU rental starts billing immediately. The timer shows your current cost. Always "Terminate" the instance when done!
3

Install Mochi 1

⏱️ 10 minutes

Once your instance is running, you'll see connection options. We'll use Jupyter or terminal access.

Method A: Using Jupyter Notebook (Easiest)

  1. Click "Connect to Jupyter Lab" button
  2. Create new notebook (Python 3)
  3. Copy and run this installation code:
!pip install transformers diffusers accelerate torch
!pip install git+https://github.com/genmoai/models.git

from diffusers import MochiPipeline
import torch

# Load the model (takes 5-10 minutes first time)
pipe = MochiPipeline.from_pretrained(
    "genmo/mochi-1-preview",
    torch_dtype=torch.bfloat16
)
pipe = pipe.to("cuda")

print("✅ Mochi 1 loaded successfully!")

Method B: Using Terminal

  1. Click "Connect to SSH" (or use terminal in Jupyter)
  2. Run these commands:
pip install transformers diffusers accelerate torch
git clone https://github.com/genmoai/models.git
cd models
python setup.py install
4

Generate Your First Video

⏱️ 5 minutes

Now the fun part - let's create a video!

# Your prompt
prompt = "King Henry VIII sits on throne, looking confused at smartphone in his hand, Tudor palace background, cinematic lighting, 16th century costume, comedic expression"

# Generate video (takes 2-5 minutes)
print("🎬 Generating video... This takes 2-5 minutes.")
video = pipe(
    prompt=prompt,
    num_frames=84,  # ~5 seconds at 16fps
    height=480,
    width=848,
    num_inference_steps=50
).frames[0]

# Save the video
output_path = "henry_confused.mp4"
from diffusers.utils import export_to_video
export_to_video(video, output_path, fps=16)

print(f"✅ Video saved to: {output_path}")

Download Your Video

  1. In Jupyter: Right-click the .mp4 file → "Download"
  2. Via SSH: Use `scp` or download through RunPod file manager
5

Important: Terminate Instance!

⏱️ 1 minute
⚠️ CRITICAL: Always terminate your GPU instance when done! Forgetting costs $0.50-1/hour even when idle.
  1. Go back to RunPod dashboard
  2. Click "Terminate" on your instance
  3. Confirm termination
  4. Your files are deleted, but you saved them locally
💡 Pro Tip: Set a calendar reminder 30 minutes after starting a GPU instance. This prevents expensive mistakes!

🚀 Advanced Open Source Techniques

LoRA Fine-Tuning

Train the model on your specific historical characters or visual style. Makes output more consistent with only 20-50 example images.

Tools: Kohya_ss, EveryDream2

ComfyUI Workflows

Visual node-based interface for chaining multiple models together. Create complex pipelines without coding.

Tools: ComfyUI, A1111 WebUI

Batch Processing Scripts

Generate 10-50 videos overnight with automated scripts. Perfect for creating multiple variations or testing prompts.

Language: Python, Bash

Model Merging

Combine strengths of different models. Merge a character-specialized model with a scene-generation model for best results.

Tools: sd-webui model merger

💰 Total Cost Comparison (1 Year)

Scenario Commercial Tools Cloud GPUs Own Hardware
Hobbyist (5 videos/month) $348/year
(HeyGen $29/mo)
$20/year
($1.65/mo GPU)
$800 one-time
(RTX 3060 build)
Regular Creator (15 videos/month) $600/year
(HeyGen + Runway)
$60/year
($5/mo GPU)
$2500 one-time
(RTX 4070 Ti)
Pro (50+ videos/month) $1200+/year
(Multiple subs + overages)
$240/year
($20/mo GPU)
$5000 one-time
(High-end dual GPU)
💡 Break-Even Analysis:
• Cloud GPUs pay for themselves immediately
• Own hardware breaks even in 2-4 years depending on usage
• For 10+ videos/month, own hardware is best long-term investment

📚 Learning Resources

HuggingFace Hub

Central repository for all open source models, tutorials, and documentation.

Visit HuggingFace →

r/StableDiffusion

Reddit community for AI video/image generation. Active discussions on latest models and techniques.

Join Community →

Civitai

Community site for model sharing, fine-tunes, and workflows. Great for finding specialized models.

Explore Civitai →

GitHub Discussions

Each model has GitHub repo with issues/discussions. Best place for technical troubleshooting.

Browse GitHub →

🎓 You've Completed the Masterclass!

You now have three complete pathways to create AI comedy videos:

✅ Your Complete Toolkit

  • Session 1: Commercial tools for quick results (HeyGen, D-ID)
  • Session 2: Multi-scene professional workflows
  • Session 3: Open source models for cost-free production
  • ✅ Understanding of ALL 40+ major AI video tools
  • ✅ Knowledge to choose the right tool for any project

🚀 Your Next Steps

  1. Decide your path: Commercial convenience or open source control?
  2. Create your first series: Plan 5-10 episodes with recurring character
  3. Build an audience: Post consistently on 1-2 platforms
  4. Iterate based on feedback: Track what works, double down
  5. Join communities: Connect with other AI video creators

Ready to Start Creating?

The technology is here. The tools are accessible. The only thing missing is YOUR unique comedic voice.