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Routing methodologySnapshot / May 1, 2026

Routing economics methodology

The published savings scenarios use documented workload presets. They are intentionally simple and explicit about what they assume.

Open quickstart

Page index

01Preset profiles02Modeled inputs03Scenario table04Representative mix05Sources and notes

Profiles

Three documented workloads.

Each preset fixes the route mix and shows the reduction produced by that scenario—not a promise about future spend.

01

Budget

Cheap-first preset.

Max savings, highest variance.

Reduction

81%

02

Balanced

Default mixed-lane preset.

Default tradeoff between savings and quality.

Reduction

63%

03

Quality

Higher quality-floor preset.

Higher quality floor, lower savings.

Reduction

42%

Inputs

What the scenarios model.

  • 01Monthly spend models a team's current spend before Astrolabe routing.
  • 02Profiles map to a fixed lane mix assumption rather than live telemetry.
  • 03Estimator outputs round to whole dollars and stay within the documented preset multipliers.

Disclaimer

Savings vary with prompt mix, fallback rates, provider outages, token counts, and any routes you pin manually.

Read routing reference

Comparison

Scenario table.

ProfileReductionBaselineWith Astrolabe

Budget profile

Max savings, most variance.

81%$1,000$190

Balanced profile

Default tradeoff.

63%$1,000$370

Quality profile

Higher floor, lower reduction.

42%$1,000$580

Route distribution

Representative stack mix.

Stack typeBudgetBalancedQuality

Budget lane

summaries, lightweight extraction, classifier traffic

70%45%25%

Standard lane

reasoning-heavy text work, longer synthesis, tool-aware chat

22%40%45%

Premium lane

high-stakes actions, confirmations, or escalation retries

8%15%30%

Evidence

Pricing sources.

Snapshot date: May 1, 2026

  • Astrolabe routing-reference and configuration docs for lane and fallback behavior.
  • Astrolabe OSS model-roster pricing snapshot updated May 1, 2026.
  • Homepage estimator presets shown on astrolabe.run for OSS onboarding.
Open stack catalog

Implementation

Notes.

  • 01Pricing references come from Astrolabe's checked-in stack model snapshot.
  • 02Profile assumptions reflect representative route mixes across routine, standard, and high-stakes traffic.
  • 03The estimator is intended for directional planning, not for finance-grade forecasting.
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One API chooses the lowest-cost model capable of the job.

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© 2026 Astrolabe CloudOne API. Automatic routing. Lower cost.