I Made a Context Compression that Saved $$$ in Vibe Coding

The Setup (Literally 60 Seconds)

pip install copium-ai
copium wrap claude

That is it. Two commands. Now every Claude Code request routes through a local compression proxy before hitting the API. My prompts get 40-80% smaller. Same answers come back.

Where My Tokens Were Going

I ran copium stats --period month after the first week and saw the breakdown:

Almost a million tokens per day, down to 268K. The quality gate ensures nothing important was lost.

The Cost Breakdown

Anthropic Claude Sonnet pricing:

• Input: $3 per million tokens

• Output: $15 per million tokens (unchanged by compression)

• Cached input: $0.30 per million tokens (90% discount)

My savings come from two sources:

• Fewer input tokens (compression)

• More cache hits (prefix stabilization)

Wait, that is only $68/month savings on raw math. Where does the $200 come from?

The bigger savings: I stay in sessions longer without hitting compaction. Before compression, long sessions hit compaction at 35 turns, forcing context loss and repeated work. Now sessions last 55+ turns productively. Fewer repeated file reads, fewer redundant tool calls, fewer wasted output tokens on re-doing work.

Does Quality Actually Stay the Same?

I was skeptical too. Here is what I measured over 4 weeks:

• Code that compiles first try: 78% (before) vs 76% (after) = within noise

• Tests passing on first run: 62% vs 60% = within noise

• "Agent forgot something" incidents: 4.2/week (before) vs 1.1/week (after) = BETTER

The last metric surprised me. Compression actually IMPROVED context management because the agent's context window was not overflowing with garbage.

What If I Have a Copilot Subscription?

Subscription users do not pay per token directly, but you still benefit:

• Longer productive sessions (context does not fill up)

• Fewer "I need to start a new chat" moments

• Better quality in long sessions

Copium

Copium (github.com/iKislay/copium) is open source (Apache 2.0) and runs entirely locally. Your code never leaves your machine. It adds about 50ms of latency per request, which is invisible compared to the 2-30 second LLM response time.

The key features that matter for cost savings:

• Zero-config proxy (copium wrap <agent>)

• Session deduplication (catches repeated file reads)

• SmartCrusher (compresses JSON tool outputs 70-90%)

• Progressive tool disclosure (reduces schema tokens 75-95%)

• Cache alignment (increases provider cache hits 3-4x)

• Quality gate (auto-reverts if compression hurts quality)

Quick ROI Calculation

There is no reason not to try it. If it does not help your workload, copium unwrap claude removes it in one command.

Tool: github.com/iKislay/copium