A Five-Dimension Fit Test for Free vs Self-Hosted AI Coding Servers

Description and use

A team uses a five‑dimension scoring framework and a token‑logging script to decide between a free AI coding server and self‑hosting.

Problem

Teams struggle to decide between free hosted AI coding servers and self-hosted solutions because free tiers often fail when workloads exceed token limits, burstiness, or data sensitivity constraints.

Outcome

Teams can objectively assess whether a free tier suffices or if self‑hosting is required, preventing CI interruptions and compliance violations.

Workflow

• Score each of five dimensions (data sensitivity, burstiness, token appetite, latency tolerance, reproducibility) from 0‑2.
• Sum the scores and apply the decision table: 0‑3 → free tier; 4‑6 → hybrid; 7‑10 → self‑hosted or paid.
• Wrap the OpenAI‑compatible endpoint with the provided Python script to log per‑task token usage.
• Run the script over a representative week of real tasks.
• Aggregate the log with jq to compute total and average tokens per task.
• Use the average to estimate monthly cost and compare against the free allowance.
• Make a data‑driven server choice based on the score and token budget.

Evidence

Score each dimension from 0 to 2. Be conservative. When in doubt, choose the higher score.

Source

The script below wraps any OpenAI-compatible endpoint and logs usage per task.

Source