GPT 5.6 Luna pricing for meeting notes

Quick start

Call GPT 5.6 Luna with the OpenAI Python SDK:

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-5.6-luna",
    max_tokens=2000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.004000 per call at standard rates
# Input:  $0.20/MTok
# Output: $1.20/MTok

How GPT 5.6 Luna compares on cost

Per-call cost for all models scoring 50+ on meeting notes benchmarks. Hover for details.

Highest-quality affordable option: Gemini 3 Flash at $0.0100/call (2.5x the cost, 83/100 quality). GPT 5.6 Luna is already the cheapest choice for meeting notes.

What drives meeting notes cost

Transcripts are long and low-density (an hour of conversation is a lot of tokens carrying comparatively little information) while the notes that come back are short. That ratio makes this a strong fit for a fast-tier model plus the batch API: notes rarely need to exist within seconds of the meeting ending, and batch discounts apply to the whole request.

For GPT 5.6 Luna specifically, that means output tokens cost 6.0x more than input, at $1.20 vs $0.20 per MTok. At this use case’s 8,000/2,000 token split, output accounts for 60% of the $0.004000 per-call cost.

GPT 5.6 Luna quality benchmarks for meeting notes

Performance across all task types

GPT 5.6 Luna scores by task type. Meeting Notes highlighted.

Confidence scores are a third-party benchmark snapshot from week 26 of 2026. This snapshot is 17 weeks old, so treat the scores as directional and validate against your own evals.

About GPT 5.6 Luna

Other models from GPT

You can compare GPT 5.6 Luna 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