GPT 5.6 Sol pricing for categorization

Quick start

Call GPT 5.6 Sol with the OpenAI Python SDK:

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-5.6-sol",
    max_tokens=150,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.006200 per call at standard rates
# Input:  $4.00/MTok
# Output: $20.00/MTok

How GPT 5.6 Sol compares on cost

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

Cheapest viable option: GPT 5.6 Luna at $0.000340/call (95% less, 91/100 quality).

What drives categorization cost

Classification into a fixed taxonomy is token-efficient by construction: the taxonomy is the same on every call and the output is one label. Put the taxonomy in the cached prefix and the marginal cost per item approaches the cost of the item text alone. Model tier matters less here than in any other use case tracked.

For GPT 5.6 Sol specifically, that means output tokens cost 5.0x more than input, at $20.00 vs $4.00 per MTok. At this use case’s 800/150 token split, output accounts for 48% of the $0.006200 per-call cost.

GPT 5.6 Sol quality benchmarks for categorization

Performance across all task types

GPT 5.6 Sol scores by task type. Categorization 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 Sol

Other models from GPT

You can compare GPT 5.6 Sol 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