Google: Gemini 4 Argon (batch)
Analysis Summary
Google: Gemini 4 Argon (batch) is developed by Google. It launched in October 2026, making it a current-generation release. On our leaderboard it earns Frontier-tier status, ranking #5 of 703 models in our overall business-suitability ranking. For raw reasoning ability it ranks #5 of 437, putting it in among the very best models we track for overall intelligence.
Its 1M-token context window is larger than 95% of the models we list, suiting long documents, large codebases, and retrieval-heavy workloads. Crucially for business adoption, Google: Gemini 4 Argon (batch) combines tool use, function calling, vision input, and step-by-step reasoning in a single model, letting teams consolidate several use cases instead of stitching together multiple services.
At $1.00 input and $5.00 output per 1M tokens, Google: Gemini 4 Argon (batch) is mid-market priced. For organisations that want a no-compromise model for coding, analysis, and agentic automation, Google: Gemini 4 Argon (batch) is among the strongest choices available today.
The DFO score ranks models on the Artificial Analysis Intelligence Index and is refreshed as new models launch. The write-up and verdict are our own. Feedback?
Benchmarks
Artificial Analysis data refreshed Oct 14, 2026. Arena ratings from the Oct 13, 2026 text leaderboard, with style control.
Artificial Analysis has not published coding or agentic results for Google: Gemini 4 Argon (batch) yet. Until it does, the model sits below tested models on the Coding and AI Agents lists.
This model was released recently. Benchmark figures are preliminary and are likely to be updated as independent testing is finalised.
How Google: Gemini 4 Argon (batch) compares
Google: Gemini 4 Argon (batch) ranks #5 of 437 AI models we track for overall intelligence. Its 1M-token context window is larger than 95% of the models we list. At $1.00 per million input tokens it is cheaper than 25% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $1.00 | $0.001000 |
| Output | $5.00 | $0.005000 |
What would Google: Gemini 4 Argon (batch) cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
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These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Google: Gemini 4 Argon (batch) for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Google: Gemini 4 Argon (batch)
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..
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Frequently asked questions about Google: Gemini 4 Argon (batch)
How much does Google: Gemini 4 Argon (batch) cost?
Google: Gemini 4 Argon (batch) costs $1.00 per million input tokens and $5.00 per million output tokens.
What is the context window of Google: Gemini 4 Argon (batch)?
Google: Gemini 4 Argon (batch) has a context window of 1,048,576 tokens (1M).
What can Google: Gemini 4 Argon (batch) do?
Google: Gemini 4 Argon (batch) supports image/vision input, tool use, and function calling.
Who created Google: Gemini 4 Argon (batch)?
Google: Gemini 4 Argon (batch) is developed by Google and was released on October 13, 2026.