Google

Gemini 4 Argon

google/gemini-4-argon
/v1/chat/completions/v1/messages/v1beta/models/*/v1/models/*

Gemini 4 Argon 是谷歌的旗舰推理模型,专为复杂软件工程、深度数学和科学问题解决以及自主多步智能体打造。谷歌训练它能在冗长多步骤的任务中保持上下文,并将混合文本、表格、图表和图片的长文档转化为一个扎实的输出。

Input / output modalities
Not provided to Not provided
Reference input / output price
Input¥14Output¥70per 1M tokens
Context window
1M
Added to catalog
Oct 14, 2026

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
Google Vertex¥14¥70¥0.71M64K

Google Vertex

Latency
1.56s
Throughput
92 tokens/s
Context
1M

Pricing

Input
¥14/M tokens
Output
¥70/M tokens
Cached
¥0.7/M tokens

Specifications

Context
1M
Max output
64K
Supported APIs
/v1/chat/completions/v1/messages/v1beta/models/*/v1/models/*

Gemini 4 Argon code examples and API guide

Modelmesh normalizes requests and responses across service providers behind one consistent API.

Modelmesh provides an OpenAI-compatible Completion API for more than 300 models and service providers. Call it directly, through the OpenAI SDK, or with supported third-party SDKs.

Modelmesh-specific request headers in these examples are optional. When supplied, your application can appear on the Modelmesh rankings.

Supported endpointsSelect an endpoint to switch the example below.
/v1/chat/completions
from openai import OpenAI API_KEY = "$SSY_API_KEY" client = OpenAI( base_url="https://router.shengsuanyun.com/api/v1", api_key=API_KEY, ) try: completion = client.chat.completions.create( model="google/gemini-4-argon", messages=[{"role": "user", "content": "Which number is larger, 9.11 or 9.8?"}], temperature=0.6, top_p=0.7, stream=True, ) response_text = "" for chunk in completion: if chunk.choices and chunk.choices[0].delta.content is not None: content = chunk.choices[0].delta.content print(content, end="", flush=True) response_text += content except Exception as error: print(f"Request failed: {error}")
                
              

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