GPT 5.6 Terra pricing for intent detection

Quick start

Call GPT 5.6 Terra with the OpenAI Python SDK:

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-5.6-terra",
    max_tokens=100,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.001800 per call at standard rates
# Input:  $2.00/MTok
# Output: $12.00/MTok

How GPT 5.6 Terra compares on cost

Per-call cost for all models scoring 50+ on intent detection benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.000180/call (90% less, 91/100 quality).

What drives intent detection cost

Intent classification sits in the hot path of a conversational product, so latency constrains model choice more than price does: batch processing is not available to you when the user is waiting. That makes the fast tier the natural fit on both axes. The intent list is constant and belongs in the cached prefix.

For GPT 5.6 Terra specifically, that means output tokens cost 6.0x more than input, at $12.00 vs $2.00 per MTok. At this use case’s 300/100 token split, output accounts for 67% of the $0.001800 per-call cost.

GPT 5.6 Terra quality benchmarks for intent detection

Performance across all task types

GPT 5.6 Terra scores by task type. Intent Detection highlighted.

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

About GPT 5.6 Terra

Other models from GPT

You can compare GPT 5.6 Terra head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions