Phase 0: Generative Media Fundamentals · 50 min · Python · fal.ai · Replicate

API vs Self-Hosted vs Managed Platforms

The right deployment strategy depends on volume, latency, cost, control, and licensing — not on which model is newest.

What you will learn

Compare API models (Sora, Veo, Kling), self-hosted models (FLUX, SDXL, MusicGen), and managed platforms (fal.ai, Replicate, Modal)
Apply a decision framework: volume, latency, cost, control, licensing
Design a hybrid deployment: APIs for video, self-hosted for images, managed for custom workflows
Evaluate when to switch from API to self-hosted as volume grows

Objective

Frame the medium, audience, constraints, and production economics before selecting a model. In the paired studio lab, build a decision matrix tool that takes a use case (e.g., '1000 product images/day', '50 marketing videos/week') and recommends a deployment strategy (API, self-hosted, managed) with cost projections, latency estimates, and a rationale for each recommendation.

The Problem

A team deploys their image generation service using the Midjourney API. It works for 100 images/day. Then they scale to 5,000 images/day and the API cost is $500/day. They want to switch to self-hosted FLUX but they don't know Docker, GPU provisioning, or model packaging. They're stuck with an expensive API because they didn't plan their deployment strategy.

Deployment strategy is an architectural decision made early — and getting it wrong means either overpaying at scale or under-delivering at launch.

What you'll build
A decision matrix tool that takes a use case (e.g., '1000 product images/day', '50 marketing videos/week') and recommends a deployment strategy with cost projections, latency estimates, and rationale.

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Key terms in this lesson

Latency