For ML APIs
A FastAPI ML API has a specific shape: long-lived container, model weights cached in memory, persistent volume for the weights so they do not redownload, async streaming for token-by-token responses. Hostim runs this shape natively. No cold starts, no per-request billing, predictable monthly cost.
# docker-compose.yml
services:
api:
image: my-fastapi-app
command: uvicorn main:app --host 0.0.0.0 --port 8000
db:
image: postgres:16Serverless platforms are a bad fit for ML inference: cold starts reload the model, per-request billing punishes long generation, and the function timeout caps long completions. Hostim runs your FastAPI container as a normal long-lived process. Mount a persistent volume at /models and load the weights once at startup; they survive every redeploy. Async streaming responses (SSE, token-by-token) work because the container stays connected for the duration of the request. CPU and RAM scale per app — GPU support is roadmap.
Teams running model inference behind a FastAPI or Flask endpoint, typically with model weights cached on disk.
Hostim runs containers as long-lived processes. Model weights stay in memory. Persistent volumes hold the weights so a redeploy does not redownload 5 GB. CPU and RAM scale per app — GPU support is roadmap.
FastAPI hosting means running a Uvicorn or Gunicorn-Uvicorn worker process and exposing it over HTTPS. The framework is async by default, so the host has to support long-lived connections — websockets, server-sent events, streaming responses.
Hostim runs your FastAPI Docker image as a normal container. Long-lived connections work. Managed PostgreSQL is attached at runtime. If you serve an ML model, mount a persistent volume for the weights so they do not redownload on every deploy.
Cold starts from serverless platforms are not a fit for ML inference workloads. Hostim runs a permanent container, so model weights stay in memory across requests.
DATABASE_URL, OPENAI_API_KEY, MODEL_PATH, LOG_LEVEL
Questions
Mount a persistent volume at /models. Download or build weights into the volume once; subsequent deploys mount the same volume — no redownload.
Yes. FastAPI on Hostim runs as a long-lived process behind HTTPS. SSE and token-by-token streaming work without extra config.
Not yet. CPU inference with enough RAM works for many smaller models (embeddings, classical ML). GPU is on the roadmap; ask if you need it for evaluation.
Hostim charges by reserved CPU, RAM and storage — flat per month. Inference cost does not scale with the number of requests; the bill is predictable.
Spin up an app in minutes. Managed database on the free tier, custom domain included.
Platform figures from the published price list, docs and our own benchmark.
€2.50/month
Hostim entry app plan
Plan sa-1-1: 1 vCPU, 1 GB RAM. Flat price, billed hourly, no usage meter.
€0
Managed database free tier
PostgreSQL 256 MB, MySQL 256 MB, Redis 128 MB, volume 1 GB. No cap on how many free instances you create.
Included on every plan
Database high availability
PostgreSQL and MySQL run as a primary plus hot standby with automatic failover, shared plans included.
2,708 TPS
Managed PostgreSQL write throughput
pgbench, 4 clients, 300 s, plan drp-50 (2 vCPU / 4 GB). AWS RDS db.t4g.medium scored 1,080 TPS on the same test.
€0/GB
Traffic charges
No ingress fees and no per-GB egress line on app plans.
1 today (Falkenstein, Germany)
Regions
Bare metal, EU only, with more regions planned. No AWS, GCP or Azure underneath.
“Managed PostgreSQL runs as a replicated cluster with automatic failover on every plan, shared and dedicated alike.”
— Hostim.dev docs, managed PostgreSQL