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Favicon for google

Google: Gemini 4 Argon

google/gemini-4-argon

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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 long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

Modalities
In / Out Price
50% off
$2 / $10per 1M
Context
1.0M
Released
Oct 13, 2026
Compare
ProvidersPricingPerformanceUptimeAppsActivityDocumentationFAQExplore

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Google: Gemini Pro versions

Not currently available through EU in-region routing. In-region routing docs

Documentation

Guides, cookbooks, blog posts, and tools for building with Google: Gemini 4 Argon on OpenRouter.

  • Gemini 4 Migration GuideCookbook

Explore more models

AI Models with Vision: Multimodal LLMs for Image UnderstandingCollectionAI Model RankingsRanking
Latency / throughput
50% off
$4.00$2.00$20.00$10.00$0.20$0.10$0.20$0.105.44s47 tps
99.56%
50% off
$4.00$2.00$20.00$10.00$0.20$0.10$0.20$0.106.00s36 tps
92.56%
Not used in Standard routing:Why these endpoints are not used
Flex50% off
$2.00$1.00$10.00$5.00$0.10$0.05$0.10$0.055.01s43 tps
100.00%
50% off
$4.40$2.20$22.00$11.00$0.22$0.11$0.22$0.115.62s43 tps
99.21%
Priority50% off
$7.20$3.60$36.00$18.00$0.36$0.18$0.36$0.183.94s29 tps
100.00%
Priority50% off
$7.20$3.60$36.00$18.00$0.36$0.18$0.36$0.18----
98.96%
Throughput
47tok/s

P50, best across providers

Latency
3.94s

P50, best provider

AutoExacto benchmarks
GPQA DiamondTAU-BenchGoogle Vertex96.5%78.7%
Uptime (3d)The model was reachable. Request routed to a provider.
100.00%
Availability (3d)The model returned inference from any provider. Errors and empty responses count against it.
97.83%

Availability over the last 3 days

Last 72 hours
Availability 97.83%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
98.65%
Without Routing
94.25%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

1.
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Claude Code
Claude Code is Anthropic's agentic coding tool that reads your entire codebase, plans and executes changes across files, runs tests, and iterates on failures, all from natural language prompts.
195Btokens
2.
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Hermes Agent
Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.
171Btokens
3.
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omp
new
68.9Btokens
4.
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pi
There are many coding agents, but this one is yours.
62.5Btokens
5.
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Freebuff
Powerful coding models, funded by ads
51.4Btokens

Frequently asked questions

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 long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output.

The Gemini 4 Argon documentation on OpenRouter includes the Gemini 4 Migration Guide cookbook. The quickstart covers API keys and your first request, and the API reference lists every parameter.

Gemini 4 Argon costs $2.00/M input tokens and $10.00/M output tokens, with separate rates for Cache Read at $0.10/M tokens, Cache Write at $0.1875/M tokens, Image Input at $2.00/M tokens, Input Audio at $2.00/M tokens, Input Audio Cache at $0.10/M tokens, and Web Search at $14.00/1K calls.

Gemini 4 Argon has a 1,048,576 token context window. It supports up to 1,048,576 completion tokens.

Yes. Gemini 4 Argon accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

Gemini 4 Argon accepts audio, files such as PDFs, images, text, and video as input and returns text.

Gemini 4 Argon is served by 2 providers on OpenRouter: Google AI Studio and Google Vertex. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

Gemini 4 Argon was released on October 13, 2026.