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Cost anatomy

GPT-6 Luna

OpenAI / Azure OpenAI · OpenAI direct APIDirect API

Fresh input / cached input / output cost breakdown, active and scheduled rates, provenance, same-model deployment markup, and cost-comparable alternatives for this purchasable lane.

Start with a pattern

Illustrative workloads

Pick a useful starting shape, then fine-tune every input below.

Fine-tune

Workload and pricing scenario

Adjust the token shape, cache behavior, time window, and service tier. Every number below updates immediately.

Interactive

Workload cost calculator

60M
210K
90%

Share of input tokens served from cache. Applied only to models with a cache meter.

Time

Rows with a rate that changes by time of day, promo window or service tier are priced for this scenario instead of their flat listed rate; a brand-colored label under the model name names which one applies. Context size for band-priced rows uses the input-token count below.

Picking a specific hour also previews time-of-day rates that are scheduled but have not started billing yet; those rows are labelled · preview with their start instant. Now only ever shows rates that are billable at this moment.

Rate state

What this lane charges right now

Priced under the workload and scenario above. The full published schedule below always shows every variant regardless of which scenario is selected.

Input / 1M
$0.10
CHF 0.081
Cached input / 1M
$0.01
CHF 0.008
Output / 1M
$0.50
CHF 0.403
Full published schedule
Batch$0.05 / $0.005 / $0.25Flex$0.05 / $0.005 / $0.25Fast mode$0.20 / $0.02 / $1.00
Cost anatomy

Where this workload's cost goes

60M input tokens (90% cache hit) and 210K output tokens, at the resolved rate above.

$0.60
Fresh input · CHF 0.483
$0.54
Cached input · CHF 0.435
$0.105
Output · CHF 0.085
$1.25
Workload total · CHF 1.00

$0.60 + $0.54 + $0.105 = $1.25

Provenance

How much to trust these numbers

InputofficialCached inputofficialOutputofficial

Global Standard short-context rate for prompts up to 272K input tokens. Prompts above 272K use the long-context row below. Batch and Flex are half price; Fast mode is 2x. OpenAI's optional regional-processing premium is not represented as a separate Direct lane.

OpenAI's official GPT-6 Luna model page (developers.openai.com/api/docs/models/gpt-6-luna), captured 2026-09-23: standard pricing is $0.10/M input, $0.01/M cached input, and $0.50/M output below 272K prompt tokens, with a 1,050,000-token context and 128,000 max output. Cache writes are outside this schema.

Azure Retail Prices API — Foundry ModelsRate effective 2026-09-22Catalog audited 2d ago — current
Direct vs Foundry

Same-model deployment markup

How much more Microsoft Foundry charges for this exact model, over this Direct rate.

LaneDeploymentWorkload costFoundry markup
GPT-6 LunaFoundry ·Data Zone$1.37+$0.124 (+10%)
GPT-6 LunaFoundry ·Global$1.25$0.00 (0%)
Cost-comparable

Other lanes within ±25% of this workload's cost

Same provider first, then ranked by cost proximity, for 60M in / 210K out. This is a cost ranking only — never a quality recommendation.

Keep exploring
OpenAI / Azure OpenAI pricing →Back to compare →