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Gemini 4 Argon

Beta ⧉
gemini-4-argon

Gemini 4 Argon Beta supports streaming text chat and Low, Medium and High thinking levels; Low is the default. Thinking tokens are billed as output. With web search on, the model looks things up with Google Search and cites its sources; each search costs $0.0035. The official context is about 1 million tokens shared by input and output, and it passed our long-input retrieval test. Repeated long inputs have produced implicit cache hits. Only actual hits receive the cached rate; a hit is not guaranteed on every repeat.

BetaLow / Medium / High1M contextOpenAI compatible

Why this model

Gemini 4 Argon Beta: three thinking levels, Google Search and a shared million-token context

Highlights

  • Beta · reasoning · Google Search
  • Low / Medium / High
  • About 1M-token context · shared input and output
  • Implicit cache hits observed on repeated long inputs. Actual hits cost $0.05 per million tokens; each repeat may differ.

Price vs. official list

KovAPIList price Input$0.5$2 Output$3$10

Per 1M tokens, USD · You save ↓70%

Use cases

Large codebase work: migrations, refactors and multi-file bug fixing
Long agent runs that plan, call tools and check their own work over many steps
Legal and financial analysis across long contracts, filings and document sets
Defensive security: finding, validating and patching software vulnerabilities

Live Test · Playground

Try out Gemini 4 Argon right here (available after login).

Input

Advanced
Web search
Memory · multi-turn

Conversation

Start a conversationType a message below to begin

About Gemini 4 Argon

Gemini 4 Argon Beta supports streaming text chat and Low, Medium and High thinking levels; Low is the default. Thinking tokens are billed as output. With web search on, the model looks things up with Google Search and cites its sources; each search costs $0.0035. The official context is about 1 million tokens shared by input and output, and it passed our long-input retrieval test. Repeated long inputs have produced implicit cache hits. Only actual hits receive the cached rate; a hit is not guaranteed on every repeat.

FAQ

How do I turn on web search?
Add "web_search": true to the request, or pass {"type": "web_search"} in tools; you can also switch it on in Advanced settings on this page. The model searches with Google Search. Sources are returned in message.annotations and the number of searches in usage.server_tool_use.web_search_requests. Each search costs $0.0035 on top of the normal token charge; the model decides whether and how often to search.
How do I control thinking?
Set reasoning_effort to "low", "medium" or "high" in the OpenAI-compatible request, or use Advanced settings on this page. Default: low. All levels use the same token rates; additional thinking consumes additional output tokens.
What is the context window?
The official context is about 1 million tokens shared by input and output. It passed our long-input retrieval test; the full window and million-token output remain untested.
Do repeated requests hit the cache?
Repeated long inputs have produced implicit cache hits. Actual hits cost $0.05 per million tokens; a hit on every repeat is not guaranteed.
What does Beta cover?
Beta currently covers text chat, streaming, three thinking levels and Google Search. Cache hits, million-token long decode, function calling and multimodal input are not promised. max_tokens is a requested target; it was not enforced as a hard output cap in our test. Use prompt length constraints and split work to manage budgets.

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