See the difference at a glance

Compare total token consumption with and without CTX across your agent fleet.
Claude Sonnet 4.6 · 1000K context · $3.00/1M input

1
No Optimization1,000,000 tokens100%
Raw context — every token stays in the window
Provider Compaction750,000 tokens75%
Lossy summarization (Claude, Cursor, etc.)
With CTX40,000 tokens4%
CTX-native compression + external memory
Tokens saved960,000
Estimated savings$3/100 turns
Claude Sonnet 4.6 pricing ($3.00/1M input tokens). Coordination overhead modeled from multi-agent architectural patterns.
CTX assumes Tier 3+ with structured memory (sub-agent rollup, orchestrator state tracking).

Detailed ROI Calculator

Fine-tune your fleet configuration and adoption tier for precise savings projections.

Configuration

Adoption Tier
Tier 3: CTX Responses: CTX response encoding. Compresses tool response data fed back to agents.
Quick Presets

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AgentCTX Assessment

Claude Sonnet 4.6 · Tier 3: CTX Responses
Input / Gateway
91% Saved
-23,875,000 tokens
$71.63/day
Output (5× cost)
76% Saved
-2,175,000 tokens
$32.63/day
CTX Response
77% Saved
-7,420,000 tokens
$22.26/day
Memory & Coordination
Unlock T4
0 tokens
$0/day
Daily Sessions (all agents)2,000
Tokens Saved / Session16,735
Overall Compression86.6%
Tokens Saved Daily33,470,000
Dollar Savings by Category

How the Savings Stack Up

AgentCTX saves tokens across four adoption tiers — each layer compounds on the last.

Gateway consolidates tool schemas and context reads before the agent sees them. CTX Grammar replaces verbose JSON tool calls with compact structured invocations. Response Encoding compresses tool response data fed back to agents. Memory & Coordination eliminates redundant context re-injection across sessions and agent fleets.

Savings = Σ (Tokens Saved per Category × Cost per Token)

Output tokens cost up to 5× input tokens — which is why even small output savings have outsized dollar impact.

Disclaimer: All savings projections are based on internal benchmarks, architectural modeling, and current provider pricing as of March 2026. Actual results may vary depending on workload type, agent coordination topology, model selection, and adoption tier. Multi-agent coordination overhead is modeled from established architectural patterns (sub-agent result rollup, orchestrator state tracking) and represents typical scenarios, not guaranteed outcomes. Model pricing reflects publicly available rates and is subject to change by providers.