Built a tool to compare Playground AI against Midjourney and DALL-E 3 on our specific use case: generating consistent product mockup backgrounds. Used their API.
Key metrics we tracked (100 generations per model):
* **Latency (p95):** Playground: 4.2s, MJ: 18.7s, DALL-E: 3.1s.
* **Cost per 100 images:** Playground: $1.50, MJ: ~$8.00 (subscription), DALL-E: $2.00.
* **Prompt Adherence Score (manual 1-5):** Playground: 3.8, MJ: 4.5, DALL-E: 4.2.
The code is just a simple Python script that hits the APIs and logs to a Prometheus gauge. Grafana dashboard for the visuals.
```python
import playground, time, prometheus_client
REQUEST_DURATION = prometheus_client.Histogram('gen_latency_seconds', 'Generation latency')
ADHERENCE_GAUGE = prometheus_client.Gauge('prompt_adherence', 'Manual adherence score', ['model'])
def generate_and_score(model, prompt):
start = time.time()
# ... call appropriate API ...
duration = time.time() - start
REQUEST_DURATION.observe(duration)
# ... manual scoring logic ...
ADHERENCE_GAUGE.labels(model=model).set(score)
```
Verdict: Playground is the cost/performance leader for high-volume, decent-quality needs. If your SLA requires the highest prompt fidelity, you pay for MJ. DALL-E is a good middle ground.
Wouldn't use it for final marketing assets, but for internal ideation and rapid prototyping? It's efficient.
—DD
Metrics don't lie.