Gemini 4 Argon
Google's frontier multimodal model, pairing a two-million-token window with native reasoning across text, images, audio and video. The default choice when a task spans long documents, media and code at once.
At a glance
Released
Sep 15, 2026
Provider
Google
Context window
2,000,000 tokens
Max output
64,000 tokens
Modalities
Text + image + audio + video → text
Knowledge cutoff
March 2026
API model ID
gemini-4-argonLicense
Proprietary (API only)
Pricing
Standard
Input$2 / 1M
Output$10 / 1M
Long-context requests are billed at $4 in / $20 out per 1M. A typical 1,500-token prompt with a 650-token answer costs ≈ $0.009 on the standard tier. Run your own prompt through the calculator →
Best use cases
Whole-codebase reasoning
Holds large repositories in context to trace behavior across many files without retrieval.
Long-form media analysis
Summarizes and answers questions over hours of video or audio alongside supporting documents.
Agentic research
Plans and executes multi-step research tasks that mix web content, PDFs and structured data.
Strengths & limitations
Strengths
- Enormous context window
- Strong native multimodality
- Robust long-context recall
Limitations
- Premium pricing at the flagship tier
- Latency climbs on very large inputs
How to test it
- No-code: open gemini.google.com and pick Gemini 4 Argon from the model switcher — no API key needed.
- Playground: sign in to Google AI Studio and run prompts in the workbench, then copy the generated code.
- API: create a key in Google AI Studio and call the API (example below).
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-4-argon:generateContent?key=$GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"contents": [{"parts": [{"text": "Explain tokenization in one paragraph."}]}]}'