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The Distillery

Optimize claude-opus cost with Claude Code

Opus is 5× more expensive than Sonnet per input token. Teams that use it for complex tasks can hit $3,600/month before realizing how fast sessions compound.

What claude-opus costs per session

Claude Opus pricing (as of April 2026) is $15.00 per million input tokens, five times the cost of Sonnet. The same 30-turn session that costs $4.50 on Sonnet costs $22.50 on Opus. Context accumulation works the same way on both models: every turn re-sends everything that came before it.

30 turns × 50,000 tokens = 1.5M input tokens/session
1.5M × $15.00/M = $22.50 per session
160 sessions/month = $3,600/month
After 40% Distillery reduction (standard session): $2,160/month (saving $1,440/month) — heavier sessions save more, up to ~85%

Why claude-opus bills compound

Developers reach for Opus when the task demands it, for complex architecture decisions, subtle debugging, long horizon reasoning. These tasks produce longer sessions. Longer sessions accumulate more context. More context means more tokens re-sent on every subsequent turn. The premium model gets the hardest sessions, which are also the sessions that accumulate context fastest.

The combination is significant. A team running 160 Opus sessions per month does not have a small API bill. It has a $3,600/month problem. And because Opus is often switched on for specific high-stakes tasks, the cost is invisible until the invoice arrives.

How The Distillery reduces claude-opus spend

Context distillation applies regardless of which model you use. The Distillery intercepts every request, Sonnet, Opus, or Haiku, and strips redundant context before forwarding. Real world cost reduction is 30-60% depending on session patterns. Because Opus sessions tend to be longer and more agentic, they contain more distillable material. Standard sessions see a 40% reduction; long Opus sessions often see higher reductions (up to ~85%).

At $3,600/month, a 40% reduction (standard session) is $1,440/month in direct API savings — real world savings of 30-60% would scale proportionally. The proxy intercepts at the network layer, with no prompt changes, no model switching, no workflow adjustment required.

See the exact methodology: benchmark results →