GPT · Fast / Budget · 1,000K context window

GPT 5.6 Luna pricing for resume parsing

$0.007300 per call at 2,500 input / 800 output tokens.

Per call

$0.007300

10K calls/mo

$73

Cache savings

90% off input

Batch savings

50% off all

Calculate your GPT 5.6 Luna costs

Adjust token counts, volume, and discount toggles to model your resume parsing spend. Pricing updated weekly.

Configure your usage

2,500
100100K
800
5050K
10,000
1001M

Estimated cost

Monthly cost
$73
10,000 calls/month
Cost per call$0.007300
Daily cost$2
Input rate$1.00/MTok
Output rate$6.00/MTok
Analyze your real spend

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=800,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.007300 per call at standard rates
# Input:  $1.00/MTok
# Output: $6.00/MTok

How GPT 5.6 Luna compares on cost

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

Cheapest viable option: Gemini 3.5 Flash-Lite at $0.001825/call (75% less, 83/100 quality).

Complete GPT 5.6 Luna pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$1.002,500
Output$6.00800

Prompt caching: 90% off input tokens

Caching drops input cost from $1.00 to $0.10/MTok. For repeated system prompts, that saves $0.002250 per call.

Batch API: 50% off all tokens

Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.007300$73$50.5$22.5
50,000 calls$0.007300$365$252.5$112.5
100,000 calls$0.007300$730$505$225
500,000 calls$0.007300$3,650$2,525$1,125
1,000,000 calls$0.007300$7,300$5,050$2,250

GPT 5.6 Luna quality benchmarks for resume parsing

GPT 5.6 Luna is a solid pick for resume parsing

Scores 89/100 (rank #2 of 14). Good balance of quality and cost for resume parsing.

Top-ranked: GPT 5.6 Terra (90/100) at $0.0183/call

Performance across all task types

GPT 5.6 Luna scores by task type. Resume Parsing highlighted.

Classification91Extraction *89Q&A85Summarization84Code Generation70Code Review68Reasoning63Creative Writing58
Task typeConfidence scoreRank out of 14
Classification91/100#1
Extraction(current page)89/100#2
Q&A85/100#4
Summarization84/100#4
Code Generation70/100#6
Code Review68/100#6
Reasoning63/100#6
Creative Writing58/100#7

Alternative models for resume parsing

13 models score 80+ on resume parsing benchmarks, sorted by input rate. Cheapest: Gemini 3.5 Flash-Lite (75% less, 83/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs GPT
Gemini 3.5 Flash-LiteGemini$0.25$1.5083/100$0.00182575% cheaper
Gemini 3 FlashGemini$0.50$3.0086/100$0.00365050% cheaper
Claude Haiku 4.5Claude$1.00$5.0088/100$0.00650011% cheaper
Gemini 3.5 FlashGemini$1.50$9.0090/100$0.011050% more
Claude Sonnet 5Claude$2.00$10.0088/100$0.013078% more
Gemini 3.1 ProGemini$2.00$12.0085/100$0.0146100% more
GPT 5.4GPT$2.50$15.0089/100$0.0183150% more
GPT 5.6 TerraGPT$2.50$15.0090/100$0.0183150% more
Claude Sonnet 4.6Claude$3.00$15.0086/100$0.0195167% more
Claude Opus 4.8Claude$5.00$25.0082/100$0.0325345% more
GPT 5.5GPT$5.00$30.0087/100$0.0365400% more
GPT 5.6 SolGPT$5.00$30.0088/100$0.0365400% more
Claude Fable 5Claude$10.00$50.0085/100$0.0650790% more

About GPT 5.6 Luna

Provider

GPT

Tier

Fast / Budget

Context

1,000K tokens

Released

Jul 2026

Other models from GPT

ModelTierInput $/MTokOutput $/MTokContext
GPT 5.5Flagship$5.00$30.00128K
GPT 5.4Mid-tier$2.50$15.00128K
GPT 5.6 SolFlagship$5.00$30.001,000K
GPT 5.6 TerraMid-tier$2.50$15.001,000K

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

How much does GPT 5.6 Luna cost for resume parsing per API call?

$0.007300 per call at 2,500 input / 800 output tokens.

Is GPT 5.6 Luna the best model for resume parsing?

Scores 89/100, rank #2 of 14 models. Top-ranked: GPT 5.6 Terra at 90/100.

What is the cheapest model for resume parsing with good quality?

Gemini 3.5 Flash-Lite scores 83/100 quality at $0.25/$1.50 per MTok. That is 75% less than GPT 5.6 Luna per call.

How can I reduce my GPT 5.6 Luna costs for resume parsing?

Three strategies: prompt caching (90% off input), batch API (50% off all tokens), prompt optimization. Combined: $0.007300 drops to about $0.000365 per call.

How does GPT 5.6 Luna pricing compare to other GPT models?

GPT also offers: GPT 5.5 at $5.00/$30.00, GPT 5.4 at $2.50/$15.00, GPT 5.6 Sol at $5.00/$30.00, GPT 5.6 Terra at $2.50/$15.00.

What context window does GPT 5.6 Luna support?

1,000K tokens total. Typical resume parsing calls use 2,500 plus 800 tokens, well within limits.

Track what you spend on AI

This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.