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CostPerPrompt

GPT-5.6 Luna (batch) API Pricing

OpenAI · context window 1.1M · prices updated 2026-08-23

Input per 1M tokens
$0.1
Output per 1M tokens
$0.6
Cached input per 1M
$0.01
90% cheaper than fresh input

Where GPT-5.6 Luna (batch) sits on price

At $0.6 per million output tokens, GPT-5.6 Luna (batch) is a mid tier model — 3.8× cheaper than the median output price of $2.25, which puts it cheaper than 80% and pricier than 20% of the models we track. It sits 12th cheapest of the 93 OpenAI models we track. Output costs 6.0× input, the usual spread — trim both, starting with the answer length.

Output tokens per $1
1,666,667
One full context fill
$0.105
Cheaper than
80% of tracked models

Cached input is 90% cheaper. On an input-heavy workload you need roughly a 28% cache-hit rate to take 25% off the input line — reachable for chatbots and agents that resend the same system prompt and history.

What real workloads cost on GPT-5.6 Luna (batch)

These three workloads are the ones teams actually run on a mid-priced model — a $0.6/1M model is not bought for the same job as one ten times the price.

Workload Per request Per month
Support chatbot — 500 conversations/day (5K in / 1.4K out) Conversation history re-sent each turn — the classic prompt-caching win. $0.0013 $20.10
Document pipeline — 10K docs/day (3K in / 500 out) Batch-friendly: no user waiting, so a ~50% batch discount usually applies. $0.0006 $180
Long-context analysis — 200 runs/day (250K in / 4K out) Only possible on large-context models; input cost is nearly the whole bill. $0.0274 $164

Model your exact traffic in the API cost calculator — it preloads GPT-5.6 Luna (batch) with caching and batch options.

GPT-5.6 Luna (batch) price history

GPT-5.6 Luna (batch)'s price has not moved since we began tracking it on Aug 6, 2026 — 17 days of stability in a market where 55 of the 302 models we track have repriced over the same period, including 9 of OpenAI's own 93 models.

Change-points from our daily price snapshots (tracking since Aug 6, 2026; intraday moves between snapshots are not captured).

GPT-5.6 Luna (batch) vs Command R (08-2024)

The closest-priced alternative from another vendor is Command R (08-2024) (Cohere) — priced within a rounding error on output, with $0.05 more per million input tokens. When two models land this close on price, the decision is quality on your own workload, not the price sheet: run 50 real requests through both and compare.

See Command R (08-2024) pricing →

Cheaper alternatives

More OpenAI models

Frequently asked questions

How much does the GPT-5.6 Luna (batch) API cost?

GPT-5.6 Luna (batch) costs $0.1 per million input tokens and $0.6 per million output tokens, with cached input at $0.01 per million (90% cheaper). That works out to roughly 1,666,667 output tokens per dollar.

What does the support chatbot workload cost on GPT-5.6 Luna (batch)?

Support chatbot — 500 conversations/day (5K in / 1.4K out) costs about $0.0013 per request and $20.10 per month on GPT-5.6 Luna (batch). Conversation history re-sent each turn — the classic prompt-caching win.

What does it cost to fill GPT-5.6 Luna (batch)'s 1.1M context window?

Sending 1.1M of input in a single request costs $0.105 at $0.1 per million tokens — before any output. With prompt caching that same fill drops to about $0.0105 on repeat requests. This is why large context windows are cheap to advertise and expensive to actually use.

Is GPT-5.6 Luna (batch) worth the price?

GPT-5.6 Luna (batch) sits in the middle of the market (12 of 93 by price within OpenAI). The honest test is a routing experiment: send the same 200 real requests to this model and to a tier below, and compare failure rate against the price gap — most teams find a majority of traffic never needed the pricier model.