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The Distillery

Claude Code for teams: what it costs and how to control it

API billing scales with every developer on your team. Here is what that looks like at 5, 10, and 20 seats, and what you can do about it.

The $2,400/month problem

A team of 5 developers running 8 Claude Code sessions per day, across 20 working days, generates 160 sessions per developer per month. At an average of 50,000 input tokens per session, that is 8 million input tokens per developer per month. At $3 per million tokens, each developer costs $480/month. Five developers: $2,400/month.

5 devs × 160 sessions/mo × 50,000 tokens × $3/M = $2,400/month

Per-seat costs at scale

Team sizeMonthly API cost (raw)After 20% reduction (conservative floor)Distillery feeNet saving
3 devs€1,440/mo€1,152/mo~€38/mo€250/mo
5 devs€2,400/mo€1,920/mo~€57/mo€423/mo
10 devs€4,800/mo€3,840/mo~€105/mo€855/mo
20 devs€9,600/mo€7,680/mo~€201/mo€1,719/mo

Distillery Pro: €9/mo + 10% of savings. Net saving = (raw − reduced) − Distillery fee. Based on Claude Sonnet $3/M input pricing.

Why teams spend more than solo developers

Solo developers naturally scope their sessions. A team of developers working in parallel generates simultaneous long-running sessions. One developer deep in a refactor, another debugging a production issue, a third building a new feature, all accumulating context independently. The cost scales with headcount, not just usage.

There is also the consistency problem. Solo developers develop intuitions about when to start a fresh context window. Teams do not naturally share those intuitions. Longer sessions become the default.

Per-seat pricing, not per-request

The Distillery runs locally on each developer's machine. There is no per-request pricing, no data leaving your network before optimization, and no change to the models or responses your team receives. Each developer sets one environment variable. The proxy intercepts, distils, and forwards transparently.

Real-world cost reduction is 30-60% depending on session patterns — we use the 20% conservative deterministic floor for the calculation above; real-world savings at 30-60% would scale proportionally. The exact number depends on how your team uses Claude Code.