GPT 5.6 Sol pricing for resume parsing

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=800,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0260 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 resume parsing benchmarks. Hover for details.

Cheapest viable option: Gemini 3 Flash at $0.003650/call (86% less, 86/100 quality).

What drives resume parsing cost

Resumes are longer than invoices and less uniformly structured, so input runs higher while output stays compact. Like invoice parsing this is a bulk, latency-tolerant workload where the batch API discount applies to the entire request. The parsing instructions are identical across every candidate, which puts them squarely in the cached prefix.

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 2,500/800 token split, output accounts for 62% of the $0.0260 per-call cost.

GPT 5.6 Sol quality benchmarks for resume parsing

Performance across all task types

GPT 5.6 Sol scores by task type. Resume Parsing 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 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