I needed to host a demo for my side project — a sentiment analysis API — but I didn't want to pay for inference. I deployed the same DistilBERT model to three free tiers and measured cold start, rate limits, and real-world usability for a week.
The Contenders
| HF Spaces | Replicate | Together | |
|---|---|---|---|
| Free tier | 2 vCPU, 16GB RAM | $5 credit/month | $1 credit/month |
| Cold start | ~30s (sleep) | ~5s | ~2s |
| Rate limit | None (public) | 100 req/min | 60 req/min |
| GPU option | Paid upgrade | Pay per sec | Pay per token |
| Custom domain | ❌ | ❌ | ❌ |
The Code
# Same FastAPI app deployed everywhere
from fastapi import FastAPI
from transformers import pipeline
app = FastAPI()
classifier = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
@app.post("/predict")
def predict(text: str):
return classifier(text)[0]
Results After 7 Days
| Metric | HF Spaces | Replicate | Together |
|---|---|---|---|
| p50 latency | 1,200ms | 800ms | 600ms |
| p99 latency | 4,500ms | 2,100ms | 1,800ms |
| Cold starts/day | 12 | 3 | 2 |
| Uptime | 94% | 99.2% | 99.8% |
| Setup time | 15 min | 10 min | 5 min |
HF Spaces is the most generous (truly free, no credit card) but the sleep mode kills UX for demos. Replicate has the best DX but burns credit fast. Together is fastest but $1/month evaporates in a weekend.
The Controversial Take
Hugging Face Spaces is the only real "free tier" here — the others are trials with extra steps. If you're building a portfolio project or a low-traffic demo, Spaces is unbeatable. If you need reliability, pay the $5. The gap between "free with caveats" and "actually free" is the difference between a side project and a liability.
I sketched the deployment configs with MonkeyCode: https://ly.cyberserval.tech/iIETXiF
Which free inference tier are you using for your demos?
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