Checked Oct 17, 2026
Gemini 4 Argon
Best for: Complex multi-step work: software engineering, legal and finance analysis, and long multimodal documents.
- LMArena text #1 of 416
- Reasoning
- Reads text, images, video, audio, PDFs
- Input
- $2
- per 1M tokens
- Output
- $10
- per 1M tokens
- Cached input
- $0.10
- per 1M tokens
- Context window
- 1M
- tokens in one request
- Max output
- 64K
- tokens per reply
- Released
- Oct 13, 2026
- Knowledge cutoff
- Mar 2026
- Weights
- Closed
- API and apps only
Gemini 4 Argon, Google's flagship reasoning model. Price shown is valid through Nov 30, 2026; from Dec 1, 2026 it doubles to $4 input / $20 output / $0.20 cached. Output includes thinking tokens. Implicit caching only. Context window is a unified input+output limit. Paid tier only.
What would Gemini 4 Argon cost you?
Change the numbers; the chart compares all 10 featured models at the same usage.
What it's good at
From Google's own announcements and docs, linked.
- Google reports it at the top of the Vals Index (68.9% on finance, coding, legal and tax work) and at 77.9% on DeepSWE v1.1 for long software-engineering tasks. source
- Reads text, images, video, audio and PDFs, and with long decode can write answers of up to about 1M tokens. source
- Thinking levels, function calling, structured outputs, code execution, Google Search and Maps grounding, and batch, flex and priority processing. source
Watch out for
Limits and costs worth knowing before you build on it.
- The $2 / $10 introductory price ends Nov 30, 2026; from Dec 1 it doubles to $4 / $20.
- Paid API tier only. In the Gemini app it needs a Google AI Pro or Ultra plan.
- Thinking tokens are billed as output, and the 1M window covers input and output together.
- Only implicit caching, and computer use is still in preview.
Scores
Benchmark numbers are as published by Google; we haven't rerun them. Makers use different setups, so don't compare one maker's numbers with another's. The leaderboard rank comes from public blind votes.
| Measure | Result | Source |
|---|---|---|
| LMArena text rank | #1 (1524) | Oct 15, 2026 |
| DeepSWE v1.1 (long software-engineering tasks) | 77.9% | |
| Vals Index (finance, coding, legal and tax work) | 68.9% | |
| Terminal-Bench 4.0 (agentic coding) | 57.4% |
How to start
Try it in the app
The quickest way to see if it suits your work. Open Google's app.
Get an API key
Sign up on Google's developer platform and add billing; you pay per token as shown above. Read the docs.
Call the model
Use this model ID in your Google API requests:
gemini-4-argon
Host the app you build with it
Gemini 4 Argon runs on Google's servers, but your bot, agent or n8n workflow needs a home. A small VPS is usually enough, since the heavy work happens at Google.
| Provider | From | Starting plan | Free tier | Our rating | Link |
|---|---|---|---|---|---|
| HostingerChecked | $2.99/mo | Premium (web hosting)20 GB SSD | No (30-day money-back guarantee) | Not rated | VisitOfficial site |
| DigitalOceanChecked | $4/mo | Basic Droplet 512 MiB1 vCPU · 0.5 GB RAM · 10 GiB SSD | Occasional promo credit for new users | Not rated | VisitOfficial site |
| VultrChecked | $2.50/mo | Cloud Compute Regular Performance, IPv6-only 0.5 GB1 vCPU · 0.5 GB RAM · 10 GB SSD | No free tier | Not rated | VisitOfficial site |
| Hetzner CloudChecked | $6.49/mo | CX23 (Cost-Optimized, Intel/AMD)2 vCPU · 4 GB RAM · 40 GB NVMe | No | Not rated | VisitOfficial site |
Compare with the other 9
| Model | Input / 1M | Output / 1M | Context | Arena |
|---|---|---|---|---|
| gpt-oss-120bOpenAI | $0.15 | $0.60 | 128K | #215 |
| Gemini 3.8 FlashGoogle | $0.75 | $3.75 | 1M | #9 |
| DeepSeek V4 ProDeepSeek | $1.32 | $3.96 | 1M | #56 |
| Grok 4.7xAI | $2 | $6 | 500K | #89 |
| Gemini 4 ArgonGoogle | $2 | $10 | 1M | #1 |
| GPT-6.1 SolOpenAI | $2 | $10 | 1.05M | #22 |
| Claude Sonnet 5.5Anthropic | $2 | $10 | 1M | #36 |
| Claude Opus 5.5Anthropic | $4 | $20 | 1M | #3 |
| Claude Fable 5.1Anthropic | $10 | $50 | 1M | #6 |
| GPT-6 AstraOpenAI | $10 | $50 | 1.05M | #30 |
Cheapest first, using 3 input tokens per output token.
Questions
How much does Gemini 4 Argon cost?
Gemini 4 Argon costs $2 per million input tokens and $10 per million output tokens at standard API rates, and $0.10 per million cached input tokens (US dollars, checked Oct 17, 2026). It is the 5th cheapest of the 10 models we feature.
How big is Gemini 4 Argon's context window?
1,048,576 tokens for the prompt, documents and conversation in one request. A single reply can be up to 65,536 tokens. How many words that holds depends on the model's tokenizer.
Is Gemini 4 Argon open source?
No. Google hasn't published its weights, so you use it through the Google API or apps rather than on your own hardware.
When was Gemini 4 Argon released?
Google released it in Oct 13, 2026.
What is Gemini 4 Argon's knowledge cutoff?
Google gives its training-data cutoff as Mar 2026. For later events it needs web search or documents you provide.
Sources
- Google pricing, checked Oct 17, 2026
- ai.google.dev/gemini-api/docs/models/gemini-4-argon
- deepmind.google/models/model-cards/gemini-4-argon
- blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon
- blog.google/innovation-and-ai/products/gemini-app/gemini-4-argon-availability
Facts checked Oct 17, 2026. Model names belong to their makers; AskGPU isn't affiliated with Google. Spotted something out of date? Tell us at hello@askgpu.com.