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. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.
$0.50market price $1.00
$0.025market price $0.05
$2.50market price $5.00
Throughput is how fast the model writes (tokens per second, higher is better). Time to first token is how long before the answer starts (lower is better).
Share of requests served without a server error. Client errors (4xx) do not count.
Works with the OpenAI SDK pointed at our base URL. Every parameter is in the API reference.
Daily usage of this model on NagaAI.
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.
On NagaAI, Gemini 4 Argon costs $0.50 per 1M input tokens and $2.50 per 1M output tokens. You pay only for what you use, with no subscription.
Gemini 4 Argon reads up to 1.0M tokens in one request, counting the prompt and the answer together.
Yes. Gemini 4 Argon can call your functions as tools and can answer in a JSON schema you give it.
It takes text, images, audio and files as input and returns text.
Create an API key, copy the model ID from the top of this page and send requests with the OpenAI or Anthropic SDK pointed at NagaAI. The API section on this page has a ready example.
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