Gemini 3.6 Flash vs GPT-5.6 Luna — Side-by-side pricing
Side-by-side API pricing and tokenizer details for Gemini 3.6 Flash (Google) and GPT-5.6 Luna (OpenAI).
Side-by-side pricing
| Feature | Gemini 3.6 Flash | GPT-5.6 Luna |
|---|---|---|
| Provider | OpenAI | |
| Input (per 1M tokens) | $1.50 | $1.00 |
| Output (per 1M tokens) | $7.50 | $6.00 |
| Long-context pricing | Flat rate at any prompt size | Over 272K tokens: $2.00 in / $9.00 out |
| Context caching | Yes — 90% off cached tokens | Yes — 90% off cached tokens |
| Batch API discount | 50% off | 50% off |
| Context window | 1M tokens | 1.1M tokens |
| Tokenizer | Gemini tokenizer | o200k_base (tiktoken) |
Real-world cost example
1,000 API requests per month, each with 500 input tokens and 200 output tokens (500K input + 200K output total).
Gemini 3.6 Flash
$2.2500
Input: $0.7500 +Output: $1.5000
GPT-5.6 Luna
$1.7000
Input: $0.5000 +Output: $1.2000
GPT-5.6 Luna is 24% cheaper for this workload — saving $0.5500 per month at this volume.
Frequently asked questions
No, GPT-5.6 Luna is cheaper for the typical workload above. At $1.00/1M input and $6.00/1M output tokens, it costs $1.7000 versus $2.2500 for Gemini 3.6 Flash — a 24% difference. Note that GPT-5.6 Luna switches to long-context pricing above 272K prompt tokens, so for very long prompts this gap does not scale linearly.
Gemini 3.6 Flash supports a 1M token context window. GPT-5.6 Luna supports a 1.1M token context window. A larger context window lets you include more text — documents, conversation history, or code — in a single API call.
Gemini 3.6 Flash supports context caching (90% off repeated tokens). It offers a 50% Batch API discount. GPT-5.6 Luna supports context caching (90% off repeated tokens). It offers a 50% Batch API discount.
No, they use different tokenizers. Gemini 3.6 Flash uses the Gemini tokenizer, while GPT-5.6 Luna uses o200k_base (tiktoken). Different tokenizers split text differently, so the same prompt will produce different token counts on each model — the effective cost difference may be larger or smaller than the per-token price difference alone suggests.
Gemini 3.6 Flash (Google): $1.5 input / $7.5 output per 1M tokens. GPT-5.6 Luna (OpenAI): $1 input / $6 output per 1M tokens. Rates shown before caching or batch discounts.
For an 80% output / 20% input workload — typical for code generation or long-form writing — Gemini 3.6 Flash costs $6.3000 per 1M total tokens and GPT-5.6 Luna costs $5.0000. GPT-5.6 Luna is 21% cheaper for this pattern. For your exact ratio, paste a real prompt into the calculator above.
Gemini 3.6 Flash has a 1M-token context window — approximately 750K words or ~3K pages of standard text. GPT-5.6 Luna has a 1.1M-token context window — approximately 788K words or ~3K pages. (Estimates assume ~0.75 words per token.)
Calculate costs for your actual prompt
Paste your prompt into the calculator and get exact token counts using each model's real tokenizer — all in your browser.
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