피파 한 줄 정리: Launch demo = 마케팅 자료. Demo 누가 골랐나·어떤 prompt·실패율·비용·한계 — 6 question으로 hype를 discount해. 1주일 community testing 기다려.
Every model launch comes with a carefully orchestrated marketing push: stunning demo videos, cherry-picked sample images, breathless press coverage, and influencer reactions. Evaluating a model launch is like evaluating a movie trailer — the trailer's job is to make you excited, not to give you an honest assessment. You need your own critical framework.
The Launch Hype Cycle
Excitement
▲
│ ╱╲
│ ╱ ╲ "This changes everything!"
│ ╱ ╲
│ ╱ ╲ ╱──────────────
│ ╱ ╲ ╱ Realistic
│ ╱ ╲ ╱ Assessment
│ ╱ ╲ ╱
│ ╱ ╲╱ "Actually, it's good at X
│╱ but limited at Y"
└──────────────────────────────────── Time
Launch 1 week 1 month 3 months
The Critical Evaluation Checklist
When a new model launches, run through these questions before forming an opinion:
1. Who selected the demo outputs? Company-selected demos show the model's absolute best results under optimal conditions. They don't represent typical user experience. Look for independent community testing within the first week.
2. What prompts were used? Demo images often use very specific prompts that the model was tuned for. If the company doesn't share prompts, that's a yellow flag. If they do share prompts, try running similar prompts on the previous model to see how much improvement actually occurred.
3. What was the failure rate? If a demo shows 10 stunning images, were those selected from 10 generations (impressive) or 10,000 generations (less impressive)? Companies never share this number. Independent testers who show failure cases alongside successes are more trustworthy.
4. What does it cost? A model that produces 20% better images at 5x the cost is a worse choice for most workflows. Always factor in cost per generation when evaluating improvements.
5. What are the known limitations? Every model card lists limitations. Read them. They reveal the specific weaknesses the developers themselves are aware of. If there's no model card or limitations section, be skeptical.
6. How does it perform on YOUR prompts? The only evaluation that matters for your work is how the model handles your specific use cases. A model that excels at landscapes but struggles with character illustration is irrelevant if you do character work.
- Launch demos are marketing materials, not honest assessments. Apply the same skepticism you'd apply to any advertisement.
- Wait for independent community testing before drawing conclusions. One week of diverse testing beats one day of curated demos.
- The only evaluation that matters is how the model performs on YOUR prompts for YOUR use cases.
- Always factor in cost. A marginal quality improvement at dramatically higher cost is rarely worth switching for.