Gemini 4 Argon
Pricing & Specs
Google (Gemini) · $4 input / $20 output per 1M tokens · 1.04858M context window
The per-token price never tells the full story. A typical task (1K input + 500 output tokens) on Gemini 4 Argon costs about $0.0140, roughly $14.00 per 1,000 runs. But if it needs 3x the tokens of a cheaper model to match quality on YOUR task, the economics flip. The only way to know is to benchmark it on your actual workload.
Gemini 4 Argon API Pricing
| Tokens | Price |
|---|---|
| Input | $4 / 1M tokens |
| Output | $20 / 1M tokens |
| Cached input | $0.2 / 1M tokens |
Intro pricing $2/$10 (cache $0.10) through Nov 30, 2026; registry uses permanent Dec 1, 2026 price for benchmarking. Batch and Flex at 50%. Priority at 1.8x. Implicit caching only (explicit caching not supported).
What that means in practice
Gemini 4 Argon Specs
| Spec | Value |
|---|---|
| Context window | 1.04858M tokens |
| Max output tokens | 65.536K tokens |
| Input modalities | text, image, video, audio, PDF |
| Output modalities | text |
| Reasoning model | Yes |
| Tool / function calling | Yes |
| JSON mode | Yes |
| Streaming | Yes |
| Prompt caching | Yes |
| Batch API | Yes |
Notes
Flagship reasoning model for complex software engineering, deep math/science, and autonomous multi-step agents. Thinking levels: low, medium, high. Context window is a unified input+output limit (1,048,576). Max output 65,536 default; up to 1M with long decode. Not available on Free tier or Google AI Pro plan.
FAQ
How much does Gemini 4 Argon cost?
Gemini 4 Argon costs $4 per 1M input tokens and $20 per 1M output tokens ($0.2 per 1M cached input tokens).
What is Gemini 4 Argon's context window?
Gemini 4 Argon has a 1.04858M-token context window. Maximum output is 65.536K tokens.
Can I test Gemini 4 Argon on my own task?
Yes. OpenMark lets you benchmark Gemini 4 Argon against 100+ models on your own task with real API calls, with no API keys needed, free tier available.
Is Gemini 4 Argon the right model for YOUR task?
Pricing tables can't answer that. Benchmark it against 100+ models
on your actual workload: real API calls, real costs. Free tier available.