Anthropic

Claude Sonnet 5

anthropic/claude-sonnet-5
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Sonnet 5 是 Anthropic 公司最强大的 Sonnet 类模型之一,其在各种编程、代理以及专业场景中的性能表现都非常出色。该模型支持自适应思维机制,用户可以选择不同的推理强度级别(低、中、高、最高以及超高强度)。它还具备 1 百万标记数的上下文存储能力,并且能够接受文本、图像和文件输入。Sonnet 5 采用了升级后的分词器,并配备了实时网络安全保护功能,能够阻止某些高风险的两用活动

Input / output modalities
文本 · 图像 · 文件 to 文本
Reference input / output price
Input¥14Output¥70per 1M tokens
Context window
1M
Added to catalog
Jul 1, 2026

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
Amazon Bedrock¥14¥70¥1.41M64K

Amazon Bedrock

Latency
3.72s
Throughput
105 tokens/s
Context
1M

Pricing

Input
¥14/M tokens
Output
¥70/M tokens
Cached
¥1.4/M tokens
Cache write (1 hour)
¥28/M tokens
Cache write (5 minutes)
¥17.5/M tokens

Additional pricing

Cache write
¥17.5
Cache read
¥1.4
Cache write price 5m
¥17.5
Cache write price 1h
¥28

Specifications

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

Claude Sonnet 5 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="anthropic/claude-sonnet-5", 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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