Anthropic

Claude Sonnet 4.5 Thinking

anthropic/claude-sonnet-4.5:thinking
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Claude Sonnet 4.5 是 Anthropic 迄今为止最先进的 Sonnet 模型,针对真实代理和编码工作流程进行了优化。它在 SWE-bench Verified 等编码基准测试中展现出顶尖性能,并在系统设计、代码安全性和规范遵循性方面均有所改进。该模型旨在实现扩展自主操作,保持跨会话的任务连续性,并提供基于事实的进度跟踪。 Sonnet 4.5 还引入了更强大的代理功能,包括改进的工具编排、推测并行执行以及更高效的上下文和内存管理。凭借增强的上下文跟踪和跨工具调用的令牌使用感知功能,它尤其适用于多上下文和长时间运行的工作流。用例涵盖软件工程、网络安全、财务分析、研究代理以及其他需要持续推理和工具使用的领域。

Input / output modalities
文本 · 图像 to 文本
Reference input / output price
Input¥21Output¥105per 1M tokens
Context window
200K
Added to catalog
Sep 30, 2025

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
Amazon Bedrock¥21¥105¥2.1200K64K
Google Vertex¥21¥105¥2.1200K64K

Amazon Bedrock

Latency
1.94s
Throughput
61 tokens/s
Context
200K

Pricing

Input
¥21/M tokens
Output
¥105/M tokens
Cached
¥2.1/M tokens
Cache write (1 hour)
¥42/M tokens
Cache write (5 minutes)
¥26.25/M tokens

Additional pricing

Cache write
¥26.25
Cache read
¥2.1
Cache write price 5m
¥26.25
Cache write price 1h
¥42

Specifications

Context
200K
Max output
64K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Google Vertex

Latency
0s
Throughput
0 tokens/s
Context
200K

Pricing

Input
¥21/M tokens
Output
¥105/M tokens
Cached
¥2.1/M tokens
Cache write (1 hour)
¥42/M tokens
Cache write (5 minutes)
¥26.25/M tokens

Additional pricing

Cache write
¥26.25
Cache read
¥2.1
Cache write price 5m
¥26.25
Cache write price 1h
¥42

Specifications

Context
200K
Max output
64K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Claude Sonnet 4.5 Thinking 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-4.5:thinking", 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}")
                
              

Related Models