This topic examines how differences in free-tier limits, credit/subscription pricing, and licensing across major AI image‑generation providers — notably Google, Midjourney, Stability AI and OpenAI — influence marketing teams, attribution models and commerce-focused platforms. As image generation is embedded into product design, creative testing and conversational commerce, unit costs, API rate limits and commercial rights increasingly shape which models and delivery methods marketers select. Platforms such as Pixite, The New Black, Ablo, LookBook AI and 1PX.AI illustrate common use cases: automated apparel design, mockups and virtual try‑ons, avatar creation and print‑on‑demand workflows. Verifast shows how conversational agents capture creative-driven purchase signals that need to be attributed back to specific images or prompts. Pricing structures — free credits, metered API calls, subscription tiers and enterprise licenses — affect the feasible scale of A/B tests, personalization and automated catalog generation. Stability’s open-source model ecosystem and on‑prem/self‑host options appeal to teams prioritizing control and predictable costs; Midjourney and OpenAI lead in ease of use and managed APIs; Google’s offerings are often integrated into broader cloud and data tooling. Key considerations for marketing and attribution practitioners: map per‑asset generation cost and latency to ROI, ensure commercial usage rights and metadata flow into analytics, and choose models that align with scale, control and content‑policy needs. Given shifting vendor terms and more conservative free tiers, teams should instrument creative lineage (prompt → model → asset) so conversion and lifetime value can be attributed accurately to AI‑generated assets.