Gemini 4 Argon vs GPT-6 Luna
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on October 22, 2026· 222 models
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents.
- Reasoning estimated
- Speed estimated
- Input
- Output
- Context
- 1 M tokens
- Max output
- ▲944 K
- Input, $ per 1M tokens
- $2.00
- Output, $ per 1M tokens
- $10.00
- Cache read, $ per 1M
- $0.100
- Batch (input / output)
- $1.00 / $5.00
- Tool calling
- Yes
- Released
- ▲10/13/2026
- Knowledge cutoff
- 2026-03
- API id
- google/gemini-4-argon
GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol.
- Reasoning estimated
- Speed estimated
- Input
- Output
- Context
- ▲1.1 M tokens
- Max output
- 128 K
- Input, $ per 1M tokens
- ▲$0.100
- Output, $ per 1M tokens
- ▲$0.500
- Cache read, $ per 1M
- $0.010
- Batch (input / output)
- $0.050 / $0.250
- Tool calling
- Yes
- Released
- 09/22/2026
- Knowledge cutoff
- 2026-05-18
- API id
- openai/gpt-6-luna
Which is the better API choice: Gemini 4 Argon vs GPT-6 Luna?
- GPT-6 Luna: cheapest input (95% less than Gemini 4 Argon)
- GPT-6 Luna: cheapest output
- GPT-6 Luna: largest context (1.1 M)
- Gemini 4 Argon: the newest (10/13/2026)
GPT-6 Luna costs 95% less on input and 95% less on output than Gemini 4 Argon ($0.100 / $0.500 versus $2.00 / $10.00 per million tokens). GPT-6 Luna accepts more context (1.1 M). On capabilities, only Gemini 4 Argon accepts audio. Gemini 4 Argon and GPT-6 Luna offer a batch tier at half price for jobs that do not need an immediate answer.
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With GPT-6 Luna you save $66.50 a month versus Gemini 4 Argon (95% less).
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- 4Qwen3.5-9B Qwen$1.72
- 5Ministral 3 3B 2512 Mistral$1.90
- 6Qwen3.5-Flash Qwen$2.02
Paste your prompt: tokens and cost per model
Rough estimate (about 4 characters per token). Nothing is sent to any server.
Cost of sending it 1,000 times (input only)
- 1GPT-6 Luna OpenAI$0.008
- 2Claude Haiku 5.5 Anthropic$0.008
- 3Gemini 4 Argon Google$0.152
- 4Claude Sonnet 5.5 Anthropic$0.152
- 5Claude Sonnet 5 Anthropic$0.152
- 6Claude Opus 5.5 Anthropic$0.304
- 7Claude Opus 5 Anthropic$0.380
- 8Claude Fable 5.1 Anthropic$0.760
Popular comparisons
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- GPT-6.1 Sol vs Gemini 4 Argon
- GPT-6.1 Sol vs DeepSeek V4.1 Flash 1017
- GPT-6.1 Sol vs Grok 4.7
- Gemini 4 Argon vs DeepSeek V4.1 Flash 1017
- Gemini 4 Argon vs Grok 4.7
- DeepSeek V4.1 Flash 1017 vs Grok 4.7
Frequently asked questions
Which is the better API choice: Gemini 4 Argon vs GPT-6 Luna?
GPT-6 Luna costs 95% less on input and 95% less on output than Gemini 4 Argon ($0.100 / $0.500 versus $2.00 / $10.00 per million tokens). GPT-6 Luna accepts more context (1.1 M). On capabilities, only Gemini 4 Argon accepts audio. Gemini 4 Argon and GPT-6 Luna offer a batch tier at half price for jobs that do not need an immediate answer.
Which is cheaper: Gemini 4 Argon and GPT-6 Luna?
GPT-6 Luna is cheaper: $0.100 per million input tokens and $0.500 per million output tokens, versus $2.00 / $10.00 for Gemini 4 Argon.
Which has more context: Gemini 4 Argon and GPT-6 Luna?
GPT-6 Luna accepts 1.1 M tokens of context; Gemini 4 Argon accepts 1 M.
Which is newer: Gemini 4 Argon and GPT-6 Luna?
Gemini 4 Argon was released on 10/13/2026; GPT-6 Luna on 09/22/2026.
What would 10,000 requests a month cost with Gemini 4 Argon and GPT-6 Luna?
With 1,500 input and 400 output tokens per request: Gemini 4 Argon: $70.00; GPT-6 Luna: $3.50 a month, at list price.
Where do the prices come from and how often are they updated?
From the public catalogs of OpenRouter, models.dev and LiteLLM, which publish each provider's list prices. They sync once a day and the last update date is shown above the comparison.
What does price per million tokens mean?
It is what the provider charges per million tokens you send (input) or the model generates (output). A token is roughly 4 characters. Output almost always costs more than input.
Sources: OpenRouter, models.dev and LiteLLM. Prices in USD per million tokens, list price, no volume discounts. Prompt tokens are an estimate; each provider's tokenizer may differ.