GPT 5.6 Terra pricing for json extraction

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=800,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0156 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 json extraction benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.001560/call (90% less, 89/100 quality).

What drives json extraction cost

Structured JSON output is compact and predictable, so cost is set almost entirely by how much source text you send. The schema itself is identical on every call and belongs in the cached prefix. This is also a task where a smaller model often matches a larger one: the output space is constrained by the schema, which limits how wrong a cheaper model can go.

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 3,000/800 token split, output accounts for 62% of the $0.0156 per-call cost.

GPT 5.6 Terra quality benchmarks for json extraction

Performance across all task types

GPT 5.6 Terra scores by task type. JSON Extraction 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