gemini-4-argon API pricing & access

gemini-4-argon API access

Gemini 4 Argon is Google’s flagship reasoning model for complex software engineering, mathematical and scientific problem solving, and multi-step agent workflows. It accepts text, images, video, audio and PDF inputs and produces text. Platform tests with a default API key verified automatic routing, streaming responses, a two-turn single-function tool round-trip, and image text and shape understanding through Google AI Studio.

Compare supported API endpoints and capabilities, then access gemini-4-argon through the unified API gateway.

Category

text

Context length

1048576 tokens

Maximum output

65536 tokens

Supported APIs

Gemini API, OpenAI Chat Completions API

API endpoints

POST /v1beta/models/gemini-4-argon:generateContent, POST /v1/chat/completions

Input modalities

text, image, video, audio, file

Output modalities

text

Capabilities

reasoning, vision, function calling, tools, caching

gemini-4-argon API pricing

Base input price

$2 per 1M tokens

Base output price

$10 per 1M tokens

Base prices are shown in USD before group-specific adjustments. Open the live pricing page for current access-group prices.

About gemini-4-argon

Gemini 4 Argon

Built for complex coding, mathematical and scientific reasoning, and multi-step agents. Google specifies a unified input/output context of 1,048,576 tokens and a default synchronous output limit of 65,536 tokens. Long decode beyond 64K requires a dedicated execution flow and has not been verified for ordinary platform calls.

The current base price is $2 input and $10 output per million tokens; output billing includes thinking tokens. Google currently lists introductory pricing through November 30, 2026, followed by $4 input and $20 output from December 1. Check the platform catalog and request billing records for actual charges.

Official model details · Official pricing

Use cases and prompting

Access and automatic routing

Model ID: gemini-4-argon. Use an API key with the required model and group permissions and call POST https://modelsok.com/v1/chat/completions. A default key can use the model ID directly with automatic routing; no channel suffix or forced group is required. Access, available channels and charges depend on your account and key configuration and usage records.

On October 14, 2026, platform tests with a default API key verified automatic routing, streaming, tool calling and image understanding. All five requests were served through Google AI Studio, with usage logs and deductions reconciled. The model is also configured in Google Vertex; the combined verification described here covers the Google AI Studio channel selected by these tests.

Basic request

curl https://modelsok.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"gemini-4-argon","messages":[{"role":"user","content":"Hello"}],"max_tokens":1024,"extra_body":{"google":{"thinking_config":{"thinking_level":"low"}}}}'

The example uses the output budget and thinking level from the tests. Thinking and the answer share the output budget; adjust it for your task.

Verified request patterns

• Streaming: add "stream": true and "stream_options": {"include_usage": true}. Read incremental content from SSE events. Normal completion, [DONE] and final token usage were verified.
• Tool calling: declare functions in tools. The test returned a lookup_inventory call in tool_calls; after the client executed a test function and returned its result with role: "tool" and the matching tool_call_id, the model correctly used the result in its answer. Preserve the full assistant message and its tool-call fields for the next turn, passing them back unchanged through your SDK so additional fields are retained.
• Image understanding: include type: "text" and type: "image_url" items in the user message’s content array. The image URL can be data:image/png;base64,.... The model correctly identified text, colors and shapes in the test PNG.

Native Gemini POST /v1beta/models/gemini-4-argon:generateContent is also available. The combined automatic-routing and capability acceptance tests above used the OpenAI-compatible endpoint.

Test scope: one short text response, one short stream, one two-turn single-function round-trip and one test PNG. Parallel or multiple tools, audio/video input, very long contexts and dedicated long decode were not tested in this run. These results do not establish continuous availability or equivalent verification across every channel.

How to call gemini-4-argon

gemini-4-argon is served through tbuy's unified gateway. Existing OpenAI or Anthropic SDK code keeps working: point base_url at https://modelsok.com and use your tbuy API key.

curl (OpenAI-compatible)

curl https://modelsok.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "gemini-4-argon", "messages": [{"role": "user", "content": "Hello"}]}'

Python (openai SDK)

from openai import OpenAI

client = OpenAI(base_url="https://modelsok.com/v1", api_key="YOUR_API_KEY")
response = client.chat.completions.create(
    model="gemini-4-argon",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

Related pages

• gemini-4-argon availability, latency and throughput (last 90 days)
• All Google model APIs
• Connect gemini-4-argon to Claude Code, Cursor, Cherry Studio and other clients

Frequently asked questions about gemini-4-argon

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