Model comparison

GPT-5.2 vs GPT-6 Luna

Two OpenAI tiers compared on the figures that decide which one a workload actually needs.

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

OpenAI

GPT-5.2

Balanced

OpenAI

GPT-6 Luna

Budget

AI model capability comparison
Specification	GPT-5.2	GPT-6 Luna
Provider
Provider	OpenAI	OpenAI
Tier
Tier	Balanced	Budget
Context window
Context window	400K	Winner: 1.05M
Max output
Max output	128K	128K
Input / 1M tokens
Input / 1M tokens	$1.75	Winner: $0.10
Output / 1M tokens
Output / 1M tokens	$14	Winner: $0.50
Weights
Weights	Closed	Closed
Parameters
Parameters	Not disclosedUnverified	GPT-6 low-cost tier
Reasoning levels
Reasoning levels	none, low, medium, high, xhigh	none, low, medium, high, xhigh, max
Modalities
Modalities	text, image	text, image
API model id
API model id	gpt-5.2	gpt-6-luna
Released
Released	December 11, 2025	September 22, 2026
Artificial Analysis Intelligence Index [xhigh] (2026-09-26)
Artificial Analysis Intelligence Index [xhigh] (2026-09-26)	30.4	Not verifiedUnverified
Artificial Analysis Intelligence Index [max] (2026-09-26)
Artificial Analysis Intelligence Index [max] (2026-09-26)	Not verifiedUnverified	37.3
DeepSWE 1.1 [max] (2026-09-22)
DeepSWE 1.1 [max] (2026-09-22)	Not verifiedUnverified	66.6

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

2026-09-26
Artificial Analysis
Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.
Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.
2026-09-22
OpenAI — Introducing GPT-6 Sol and Luna (vendor; not yet on Datacurve's board)
Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.
Directly comparable

Pricing tiers

GPT-5.2: Standard $1.75/$14 per MTok; cached input $0.175/MTok; batch $0.875/$7. (gpt-5.2-pro exists at $21/$168.)

GPT-6 Luna: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.

BalancedRecord checked September 26, 2026

GPT-5.2

GPT-5.2 was OpenAI's December 2025 flagship — still a widely integrated general model at $1.75/$14.

Best for

General production
Agentic workflows
Knowledge work

Watch out

Three generations behind GPT-6 — OpenAI's GPT-5.2 page recommends GPT-6 Astra; capable but no longer flagship.

BudgetRecord checked September 26, 2026

GPT-6 Luna

GPT-6 Luna is OpenAI's cheapest current model at $0.10/$0.50 — the direct successor to GPT-5.6 Luna at half the price, with the full 1.05M-token context.

Best for

High-volume chat and extraction
Classification
Cost-capped agent loops

Watch out

Small tier: it matches GPT-5.6 Luna on the Artificial Analysis index but sits well below GPT-6 Sol on hard reasoning; the DeepSWE figure is vendor-reported at max effort.

When the cheaper one wins

GPT-6 Luna is cheaper on output at $0.50 per million tokens against $14 for GPT-5.2 — about 28×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

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Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

Pricing verified on both sides — Input and output rates are verified for both models.
4/5 core specs verified on both sides — Not published for at least one side: parameter count.
1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
Verified within the last 90 days — Newest catalog check was 2 days ago.
Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

GPT-5.2: OpenAI — Introducing GPT-5.2 (accessed 2026-08-29)
GPT-5.2: OpenAI API pricing (gpt-5.2 $1.75/$14) (accessed 2026-08-29)
GPT-6 Luna: OpenAI — Introducing GPT-6 Sol and Luna (accessed 2026-09-26)
GPT-6 Luna: OpenAI model docs — gpt-6-luna (1.05M context, 128K output) (accessed 2026-09-26)
GPT-6 Luna: OpenAI API pricing (gpt-6-luna $0.10/$0.50, cached $0.01) (accessed 2026-09-26)

Related comparisons

Diving deeper on one model? GPT-5.2 · GPT-6 Luna

Common questions

GPT-5.2 vs GPT-6 Luna

Answered from the verified figures on this page rather than general guidance.

Is GPT-5.2 or GPT-6 Luna cheaper for input?

GPT-6 Luna is cheaper at $0.10 per million input tokens, against $1.75 for GPT-5.2 — roughly 18× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GPT-5.2 has tiered pricing: Standard $1.75/$14 per MTok; cached input $0.175/MTok; batch $0.875/$7. (gpt-5.2-pro exists at $21/$168.) GPT-6 Luna has tiered pricing: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.

Is GPT-5.2 or GPT-6 Luna cheaper for output?

GPT-6 Luna is cheaper at $0.50 per million output tokens, against $14 for GPT-5.2 — roughly 28× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GPT-5.2 has tiered pricing: Standard $1.75/$14 per MTok; cached input $0.175/MTok; batch $0.875/$7. (gpt-5.2-pro exists at $21/$168.) GPT-6 Luna has tiered pricing: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.

Which has the larger context window, GPT-5.2 or GPT-6 Luna?

GPT-6 Luna accepts 1.05M tokens against 400K for GPT-5.2. This only matters if you routinely send very long documents or large codebases.

Do GPT-5.2 and GPT-6 Luna support the same reasoning levels?

GPT-5.2 exposes none, low, medium, high, xhigh, while GPT-6 Luna exposes none, low, medium, high, xhigh, max.

Should I use GPT-5.2 or GPT-6 Luna?

GPT-5.2 is the balanced tier and GPT-6 Luna the budget tier. The useful question is whether your hardest task actually fails on the cheaper one — most production volume such as classification, extraction and summarisation does not.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

Input price: GPT-6 Luna costs $0.10 per 1M tokens versus $1.75 for GPT-5.2 — a 17.5x difference at the headline tier.
Context: GPT-6 Luna takes 1.05M against 400K for GPT-5.2 — only decisive if your prompts approach the smaller window.
Positioning: GPT-5.2 sits in the balanced tier, GPT-6 Luna in the budget tier — most production volume (classification, extraction, summarisation) does not need the pricier tier.

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