Output Token Limit Policy

Data artifactModel ServingModelsarc:OutputTokenLimitPolicy

A calibrated per-feature configuration of the maximum number of output tokens a model may generate, set to the smallest limit that preserves measured response quality.

Responsibility. Caps generated output length to control output-token cost.

Also known as: max_tokens constraint, Output length constraint

Direct neighbourhood (hover for relationship types)

Relationships

constrains control

LLM Inference Service Ch8.3

is produced by lifecycle

Output Length Calibrator Ch8.3

Design guidance

SHOULD be derived from the observed output-length distribution and quality testing rather than set arbitrarily.
SHOULD be paired with structured-output instructions so responses become naturally concise rather than truncated.

Quantitative guidance

As stated by the sources; verify before use.

Output distribution: p50 650, p75 800, p90 1,100, p95 1,400 tokens, mean 800 (Ch8.3).
max_tokens = 400 dropped CSAT to 3.9/5; 500, 600 and 800 all held 4.3/5; 500 selected, cutting average output 37.5% (800 -> 500) (Ch8.3).
Output constraints saved $435/month ($4,365 -> $3,930, ~10%); at 4x output pricing, 300 output tokens saved equal 1,200 input tokens (Ch8.3).

Classification

Patterns: Output length capping
Quality attributes: Performance efficiency (ISO/IEC 25010)
Risks mitigated: Verbose responses inflating output-token costMid-sentence truncation from uncalibrated limits

Sources

Ch8.3: T. Nguyen, "Token Economics and Architecture," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 8.3. ISBN: 9798244538229.