A coding assistant fires hundreds of small completions a day per developer. Each is cheap, but they add up — and the model choice swings the bill 20×. Enter your team's usage to see the API cost per developer and per month, and whether building beats a flat per-seat tool.
—per developer
—per year
—completions/mo
Cost per developer by model
Same usage, every model ranked cheapest first. Compare to a ~$10-19/seat flat tool.
| Model | Per dev / mo | Team / mo |
|---|
⚠️ Reference prices (July 2026). Real autocomplete sends a lot of file context as input (often 1-4k tokens) and short outputs — input dominates, so prompt size and model choice are the big levers. Off-the-shelf tools (Copilot, Cursor) bundle infra at a flat per-seat price. ·
Report outdated price →✓ Last verified: 2026-07-15· Source: official provider pricing page· Auto-monitored — report change →
Build vs buy
The trade-off is simple: a flat per-seat tool is predictable; a raw API can be cheaper for light use or much pricier for heavy autocomplete on a frontier model. Input dominates because every completion ships file context, so a smaller model and tighter context window are the biggest savings. Estimate a single call on the LLM token cost calculator, cache the repeated system prompt with prompt caching, and compare whole-app spend on the AI app cost estimator. This calculator models per-completion autocomplete usage — for full agentic tasks (Claude Code, Cursor Agent Mode, Codex) where one task can burn 400K-2M cumulative tokens, see the AI coding agent subscription vs API calculator instead, or the Copilot premium request calculator for GitHub's model-multiplier billing.
How this calculator works
This calculator estimates the monthly cost of running an AI coding assistant on a metered LLM API, then compares it to a flat per-seat subscription. It multiplies your number of developers by completions per developer per day and working days per month to get total monthly completions, then multiplies each completion by its input and output token counts and the selected model's per-token input and output rates. The result is a token-based figure that scales with how many developers you have, how often each one triggers a completion, and how large the prompts and responses are — so heavier usage or a more expensive model raises the bill directly, unlike a fixed per-seat price.
The key trade-off is usage volatility. A flat per-seat tool has a predictable cost ceiling, while API pricing rewards light use but can exceed a subscription when developers request many completions or the model produces long outputs. Because output tokens usually cost more than input tokens, verbose responses matter most. Try realistic high-usage numbers, not just averages, and re-check whenever you switch models — rates vary widely, and a cheaper per-token model can flip which option is less expensive at your team's actual volume.
Frequently asked questions
What does an AI coding assistant cost per developer?
A self-hosted coding assistant on an LLM API typically runs a few dollars to ~$20 per developer per month, depending on how many completions they trigger and the model. Heavy users on a frontier model cost far more than light users on a small model. Off-the-shelf tools like GitHub Copilot charge a flat ~$10-19/user instead.
Is it cheaper to build or buy a coding assistant?
For light usage, a small model via API can undercut a flat per-seat subscription. For heavy autocomplete on a frontier model, a flat subscription is often cheaper and more predictable. This calculator shows your API cost per developer so you can compare.