Prices → Compare → GPT-5.6 Luna vs Gemini 3.1 Pro
GPT-5.6 Luna vs Gemini 3.1 Pro: API cost compared
GPT-5.6 Luna lists at $0.100 in / $0.600 out per 1M tokens. Gemini 3.1 Pro lists at $2.000 in / $12.00. Sticker price only tells you so much — below is what each actually costs across eight production workloads.
Side by side
| GPT-5.6 Luna | Gemini 3.1 Pro | |
|---|---|---|
| Provider | OpenAI | |
| Input per 1M | $0.100 | $2.000 |
| Output per 1M | $0.600 | $12.00 |
| Cached input per 1M | $0.010 | not published |
| Context window | 400k | 1M |
| Blended per 1M (3:1) | $0.225 | $4.500 |
Monthly cost by workload
Caching applied at each workload's typical hit rate. This is where the two models actually separate.
| Workload | GPT-5.6 Luna | Gemini 3.1 Pro | Cheaper | Difference |
|---|---|---|---|---|
| Customer support chatbot | $14.64 | $390.00 | GPT-5.6 Luna | $375.36 (96%) |
| RAG document Q&A | $19.60 | $464.00 | GPT-5.6 Luna | $444.40 (96%) |
| Coding agent | $10.45 | $344.00 | GPT-5.6 Luna | $333.55 (97%) |
| Bulk summarization | $138.60 | $2,880 | GPT-5.6 Luna | $2,741 (95%) |
| Structured data extraction | $187.00 | $5,000 | GPT-5.6 Luna | $4,813 (96%) |
| Long-form content generation | $25.46 | $520.00 | GPT-5.6 Luna | $494.54 (95%) |
| Email triage agent | $43.25 | $1,360 | GPT-5.6 Luna | $1,317 (97%) |
| Translation pipeline | $164.47 | $3,330 | GPT-5.6 Luna | $3,166 (95%) |
How to read this
GPT-5.6 Luna is cheaper on the majority of these workloads, but "majority" is not the decision. The output:input price ratio is 6.0 for GPT-5.6 Luna and 6.0 for Gemini 3.1 Pro. If your traffic is output-heavy — long-form drafting, translation — the model with the lower output price wins regardless of what the input price suggests. If you are input-heavy — RAG, bulk summarization, agents re-reading a codebase — the cached input rate matters more than either headline number.
Cost is also not the only axis. This site does not benchmark quality, latency, or rate limits, and a model that is 3x cheaper but needs two attempts per task is not cheaper. Use these numbers to size a bill, then validate on your own evals.
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| Model | In /1M | Out /1M | Monthly | vs best |
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