OPENAI VS GOOGLE

GPT-5.6 Luna vs Gemini 3.5 Flash-Lite

GPT-5.6 Luna is about 1.9x cheaper than Gemini 3.5 Flash-Lite on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.0044 vs $0.008. Gemini 3.5 Flash-Lite has the larger context window (1,048,576 vs 1,047,576 tokens).

Pricing verified

API pricing per 1M tokens

ModelInput / 1M tokensOutput / 1M tokensBlended (3:1 mix)
GPT-5.6 Luna$0.20$1.20$0.45
Gemini 3.5 Flash-Lite$0.30$2.50$0.85

Rates from official OpenAI pricing and official Google pricing, checked 2026-08-11.

What a real workload costs

Example: one request with 10,000 input tokens and 2,000 output tokens, then that request at 100,000 runs per month.

ModelPer request (10K in / 2K out)Per month (100K requests)Monthly delta
GPT-5.6 Luna$0.0044$440—
Gemini 3.5 Flash-Lite$0.008$800+$360

Model your own prompt sizes and volumes in the token cost analyzer, or check caching savings with the prompt caching calculator.

Specs side by side

SpecGPT-5.6 LunaGemini 3.5 Flash-Lite
ProviderOpenAIGoogle
Context window1,047,576 tokens1,048,576 tokens
Model classGeneral textGeneral text
Tokenizero200k_base (exact, public)Proprietary (counts estimated)

Count tokens for each model on its own page: GPT-5.6 Luna token counter and Gemini 3.5 Flash-Lite token counter. All OpenAI models are on the OpenAI Token Counter. All Google models are on the Gemini Token Counter.

FAQ

GPT-5.6 Luna vs Gemini 3.5 Flash-Lite FAQ

Which is cheaper, GPT-5.6 Luna or Gemini 3.5 Flash-Lite?

GPT-5.6 Luna is cheaper. At rates checked 2026-08-11, GPT-5.6 Luna costs $0.20 input / $1.20 output per 1M tokens, while Gemini 3.5 Flash-Lite costs $0.30 input / $2.50 output — about a 1.9x difference on a typical 3:1 input-heavy workload.

How much does a real request cost on GPT-5.6 Luna vs Gemini 3.5 Flash-Lite?

A request with 10,000 input tokens and 2,000 output tokens costs about $0.0044 on GPT-5.6 Luna and $0.008 on Gemini 3.5 Flash-Lite. At 100,000 such requests per month that is $440 vs $800 — a difference of $360 per month.

Which has the bigger context window, GPT-5.6 Luna or Gemini 3.5 Flash-Lite?

Gemini 3.5 Flash-Lite. It supports 1,048,576 tokens of context versus 1,047,576 tokens — roughly 786,000 English words in one request.

Do GPT-5.6 Luna and Gemini 3.5 Flash-Lite count tokens the same way?

Not exactly. GPT-5.6 Luna uses the published o200k_base tokenizer and Gemini 3.5 Flash-Lite uses a proprietary tokenizer (counts are estimates). The same prompt will tokenize differently, which shifts effective cost per word.