Gemini 4 Argon — Specifications
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Developer | Google DeepMind |
|---|---|
| Type | Reasoning / agentic |
| Modality | Text, Image, Video, Audio, PDF → Text |
| Parameters | Undisclosed |
| Context window | 1M |
| Max output | 1M (long decode; 65K per default response) |
| License | Proprietary |
| Open weights | No |
| Released | 2026-09 |
| Input price | $2.00 /1M |
| Output price | $10.00 /1M |
| API providers | Gemini API (paid tier), Google Cloud (Gemini Enterprise Agent Platform) |
Benchmarks
| Google-reported | DeepSWE v1.1 77.9%; AutomationBench 51.3% (#1); LVBench 91.7%; CWE-bench v1 68% (tied first). |
|---|
What is Gemini 4 Argon?
Gemini 4 Argon is Google DeepMind’s frontier model, announced on 30 September 2026 and opened to developers on 13 October 2026. According to Google, it is built for long, multi-step work in software engineering, enterprise knowledge work such as law and finance, and cybersecurity defence, and its output limit rises to 1 million tokens from 64,000.
At announcement it was available only to trusted cyber defenders through the Fairwind Program. Since 13 October it has been generally available on the paid tier of the Gemini API and on Google Cloud’s Gemini Enterprise Agent Platform; there is no free API tier. Google AI Pro and Ultra subscribers can also use it in the Gemini app. Its context window is 1,048,576 tokens, shared between input and output. In the Gemini API a single response returns up to 65,536 tokens by default, and long decode extends the output toward the full 1M.
Price: per Google’s pricing page, Argon costs an introductory $2 per million input tokens and $10 per million output tokens through 30 November 2026, with cached input at $0.10 (95% off). From 1 December 2026 the price doubles to $4 / $20, and cached input to $0.20. Thinking tokens are billed as output, and Batch or Flex requests cost half the standard rate. Run your own token counts through the AI API cost calculator before committing.
Google announced a stronger model, Gemini 4 Carbon, on 28 October 2026. For now Carbon is limited to selected cyber defenders through the Fairwind Program, and Google says it will launch at the same introductory price as Argon, so Argon remains the most capable Gemini model developers can call. A plain-language guide: Gemini 4 Argon explained.
Gemini 4 Argon pricing: API cost per 1M tokens
| Input (per 1M tokens) | $2.00 |
|---|---|
| Output (per 1M tokens) | $10.00 |
| Output/input ratio | 5× |
| Blended (4:1 in:out) | $3.60 per 1M tokens |
What Gemini 4 Argon costs per month
Real monthly spend at a 4:1 input-to-output mix — the ratio a typical chat or RAG workload actually produces.
| Workload | Tokens / month | Cost / month |
|---|---|---|
| Side project | 1M in / 0.25M out | $4.50 |
| Small team | 20M in / 5M out | $90 |
| Production | 200M in / 50M out | $900 |
Run your own numbers in the AI API cost calculator.
Cheaper alternatives to Gemini 4 Argon
| Model | Blended $/1M | You save |
|---|---|---|
| Llama 3.1 8B open | $0.0240 | 99% cheaper |
| Mistral NeMo 12B open | $0.0292 | 99% cheaper |
| Gemma 3 4B open | $0.0600 | 98% cheaper |
Frequently asked questions
How much does Gemini 4 Argon cost per 1M tokens?
Gemini 4 Argon costs $2.00 per 1M input tokens and $10.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $3.60 per 1M tokens.
How much does Gemini 4 Argon cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $90 on Gemini 4 Argon. A side project (1M in / 0.25M out) costs roughly $4.50.
What is a cheaper alternative to Gemini 4 Argon?
Llama 3.1 8B is the cheapest model in our database at $0.0240 per 1M blended — about 99% less than Gemini 4 Argon. Cheaper models are usually smaller, so test it on your own task before switching. It is also open-weight, so self-hosting is an option.
Can I run Gemini 4 Argon locally?
No. Gemini 4 Argon is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Gemini 4 Argon charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. Gemini 4 Argon charges 5× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Prices are the published list rates for the model's primary API and are reviewed as providers change them. Volume, batch and cached-input discounts are not included. Compare every model side by side in the AI models database or the LLM leaderboard.