gpt-6-sol
Input price$2
Output price$10
OpenAITextVision
gpt-6-luna
gpt-6-luna is OpenAI's model at $0.10 input and $0.50 output per million tokens, with a 1050K context window. On a typical 3:1 input-to-output mix that blends to roughly $0.20 per million tokens, placing it in the budget band of the 82 models tracked here — cheaper than 81% of them.
Context window1050K
Input price$0.1 / 1M
Output price$0.5 / 1M
Output speed—
Quality score—
Data updatedUpdated Sep 2026
Price verified2026-09-23 · OpenRouter
By price, gpt-6-luna ranks 9th cheapest of 82 on input and 18th on output.. Its blended rate sits 94% below the catalog average.
In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $23 per month on gpt-6-luna, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $24. Because output is priced 5.0× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.
A 1050K context window holds roughly 1,400 pages of A4 text (at ~750 tokens per page), ranking 3rd of 82 here. That is enough to drop in an entire technical manual or several source files at once, which suits long-document summarization and codebase-wide analysis.
We track 14 OpenAI models, and gpt-6-luna's blended rate sits 96% below that provider's average. If your task tolerates a little less headroom, Phi-4-mini (Microsoft) blends about 88% cheaper at a quality score of 68, and is worth benchmarking first. Going the other way, qwen3.7-flash scores 82 on quality for about 73% less.
The closest model in OpenAI's line-up is gpt-4o-mini ($0.15 input / $0.60 output, quality 80). Against it, gpt-6-luna scores 80 points lower on quality, has a 922K larger context window, costs 31% less blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.
Estimated monthly cost
Monthly API spend across four common workloads, next to the cheapest model we track.
| Workload | Usage assumption | This model | Cheapest model |
|---|---|---|---|
| Support chatbot | 2,000 input / 500 output tokens per turn, 50,000 turns per month | $23 | $3.00 |
| RAG document Q&A | 8,000 input / 800 output tokens per query, 20,000 queries per month | $24 | $3.84 |
| Coding assistant | 12,000 input / 2,000 output tokens per request, 10,000 requests per month | $22 | $3.20 |
| Batch summarization | 4,000 input / 400 output tokens per item, 200,000 items per month | $120 | $19 |
Derived directly from the rates on this page. Excludes prompt caching, batch discounts and free tiers.
How it compares
The alternatives worth benchmarking alongside it, from the same dataset.
| Model | Provider | Blended /1M | Quality | Price delta |
|---|---|---|---|---|
| gpt-6-luna | OpenAI | $0.20 | — | — |
| Phi-4-miniCheaper option | Microsoft | $0.025 | 68 | -87% |
| qwen3.7-flashHigher quality | Alibaba | $0.055 | 82 | -73% |
| gpt-4o-miniSame provider | OpenAI | $0.26 | 80 | +31% |
Best for
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Modalities
TextVision
Where it fits — and where it doesn't
Good fit
- Long documents: a 1050K window ingests a full contract, paper or large codebase in one pass.
- High-volume, cost-sensitive batch work: low rates suit classification, tagging and summarization at scale.
- Multimodal input: handles images, screenshots and scanned documents directly.
Poor fit
- No obvious disqualifiers — still benchmark on your own data before committing.
Frequently asked questions
How much does the gpt-6-luna API cost?
gpt-6-luna costs $0.10 per million input tokens and $0.50 per million output tokens. On a 3:1 input-to-output mix that blends to about $0.20 per million tokens.
What does gpt-6-luna cost per month?
It depends on volume. Using the four worked scenarios on this page: a support chatbot runs about $23/month, RAG document Q&A about $24/month, a coding assistant about $22/month, and batch summarization about $120/month. Plug your own token counts into the cost calculator for a tailored figure.
How large is the gpt-6-luna context window?
1050K tokens — roughly 1,400 pages of A4 text at ~750 tokens per page, ranking 3rd of the 82 models tracked here.
gpt-6-luna or Phi-4-mini — which is better value?
Phi-4-mini blends to about $0.025 per million tokens versus $0.20 for gpt-6-luna — roughly 88% cheaper — at a quality score of 68 against —. If that quality gap does not show up on your task, take the cheaper one; if it does, stay with gpt-6-luna. Benchmark both on your own data before deciding.
What is gpt-6-luna best suited for?
Long documents: a 1050K window ingests a full contract, paper or large codebase in one pass. Less suitable: No obvious disqualifiers — still benchmark on your own data before committing.
How current is this gpt-6-luna pricing?
Pricing here was last verified on 2026-09-23 against OpenRouter. llmprice.app runs a daily collection job, but providers can change rates between runs — confirm against OpenAI's official pricing page before you commit.
Estimate the real cost of this model
Bring tokens per request and monthly volume into the calculator to compare total model costs.
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Pricing, speed and quality scores change over time. Confirm official documentation before production use.