GPT-5.6 Luna API pricing
GPT-5.6 Luna from OpenAI costs $0.20 per 1M input tokens and $1.20 per 1M output tokens. Cached input drops to $0.02 per 1M.
That puts it 15th cheapest of the 60 models tracked here on a blended 3:1 input-to-output rate, or $0.450 per 1M blended tokens. Verified 2026-08-16.
- Input
- $0.20per 1M tokens
- Output
- $1.20per 1M tokens
- Cached input
- $0.02 90% off input
- Batch discount
- None not published
- Price rank
- #15of 60, cheapest first
- Tokens per $1
- 2,222,222at a 3:1 mix
What GPT-5.6 Luna costs on a real workload
Per-million-token rates are hard to reason about, so here is the same model priced against four concrete monthly workloads. Each row uses this model's own input and output rates against a fixed token mix, with no caching or batch discount applied.
| Workload | Assumption | Monthly cost | Annual |
|---|---|---|---|
| Support chatbot | 50,000 conversations/month at 3K input and 500 output tokens each | $60.00 | $720.00 |
| RAG document search | 200,000 queries/month at 6K retrieved-context input and 400 output tokens | $336.00 | $4,032 |
| Coding agent | 5,000 runs/month at 60K input and 8K output tokens per run | $108.00 | $1,296 |
| Bulk classification | 5,000,000 items/month at 400 input and 20 output tokens each | $520.00 | $6,240 |
Your mix will differ. The API cost calculator takes your own token counts, and the cost per request calculator scales a single call up to per-1,000 and per-month totals.
Cheaper alternatives to GPT-5.6 Luna
These are the closest cheaper options from other providers, ordered by how near they sit to GPT-5.6 Luna on the blended rate. Closer is usually a more realistic swap: the further down this list you go, the more capability you are likely trading away.
| Model | Provider | Input / 1M | Output / 1M | Cheaper by |
|---|---|---|---|---|
| Llama 4 Maverick | Meta | $0.20 | $0.60 | 1.5x |
| Grok 4.1 Fast | xAI | $0.20 | $0.50 | 1.6x |
| Mistral Small 4 | Mistral | $0.15 | $0.60 | 1.7x |
| Sonar Small Online | Perplexity | $0.20 | $0.20 | 2.3x |
| DeepSeek V4 Flash | DeepSeek | $0.14 | $0.28 | 2.6x |
Before switching, price the move properly: the model switching savings calculator puts two models against the same workload and shows the annual difference.
Models priced near GPT-5.6 Luna
If cost is roughly fixed and you are choosing on capability instead, these are the models sitting closest to GPT-5.6 Luna on price.
| Model | Provider | Input / 1M | Output / 1M | Blended |
|---|---|---|---|---|
| GPT-5.4 nano | OpenAI | $0.20 | $1.25 | $0.463 |
| DeepSeek V4 Pro | DeepSeek | $0.435 | $0.87 | $0.544 |
| Llama 4 Maverick | Meta | $0.20 | $0.60 | $0.300 |
| Grok 4.1 Fast | xAI | $0.20 | $0.50 | $0.275 |
How to pay less for GPT-5.6 Luna
Prompt caching. Cache-hit input tokens bill at $0.02 instead of $0.20, which is 90% off. This matters most for workloads that resend a large, mostly-static prefix on every call: system prompts, tool definitions, retrieved documents, long conversation histories. The saving scales with your cache hit rate, so the prompt caching savings calculator is the honest way to size it rather than assuming a perfect hit rate.
About OpenAI
OpenAI sells the GPT family through a tiered lineup, from the flagship reasoning tier down to nano models built for volume, with a cached-input discount on almost every tier.
See every OpenAI model and how the lineup is tiered on the OpenAI pricing page, or put GPT-5.6 Luna against all 60 models from all 17 providers on the comparison table.
GPT-5.6 Luna pricing FAQ
How much does GPT-5.6 Luna cost per 1M tokens?
GPT-5.6 Luna costs $0.20 per 1M input tokens and $1.20 per 1M output tokens. Cached input tokens are cheaper again at $0.02 per 1M, a 90% discount on repeated context.
Is GPT-5.6 Luna expensive compared to other models?
It ranks 15 of 60 on a blended rate that weights input and output 3:1, so 14 tracked models are cheaper and 45 are more expensive. That works out to 8.2x the blended rate of Qwen3.7 Flash, the cheapest model tracked here.
What does a real workload cost on GPT-5.6 Luna?
A support chatbot handling 50,000 conversations a month at 3K input and 500 output tokens each comes to about $60.00 a month. A coding agent doing 5,000 runs at 60K input and 8K output per run comes to about $108.00. Run your own numbers in the API cost calculator.
Why is GPT-5.6 Luna output more expensive than input?
Output on this model is 6.0x the input rate. Every output token needs its own forward pass through the model, while input tokens are processed in parallel, so output costs more to serve across essentially every provider. It also means a workload's input:output mix, not just its total token count, drives the bill.
What is a cheaper alternative to GPT-5.6 Luna?
Llama 4 Maverick from Meta is the closest cheaper option at $0.20 / $0.60, roughly 1.5x cheaper on a blended basis. Whether it is a real substitute depends on whether your task actually needs the extra capability.