Anthropic

Claude Opus 4.8

anthropic/claude-opus-4.8
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Claude Opus 4.8 是 Anthropic 在 Opus 家族中最强大的通用型号。它支持文本、图片和文件输入,并输出文本,支持推理和 1M 令牌上下文窗口。它适合高度自主的代理、长视野代理工作、知识驱动工作以及在长时间会话中保持一致性的记忆驱动任务。 它在多步推理、复杂编码和端到端项目编排方面尤为强大——大型代码库、多阶段调试和长期运行的异步代理流水线。除了编码,它还处理知识工作,如起草文档、构建演示文稿和分析数据,保持长时间输出的质量。

Input / output modalities
Not provided to Not provided
Reference input / output price
Input¥35Output¥175per 1M tokens
Context window
1M
Added to catalog
May 29, 2026

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
Amazon Bedrock¥35¥175¥3.51M128K
Google Vertex¥35¥175¥3.51M128K

Amazon Bedrock

Latency
1.36s
Throughput
96 tokens/s
Context
1M

Pricing

Input
¥35/M tokens
Output
¥175/M tokens
Cached
¥3.5/M tokens
Cache write (1 hour)
¥70/M tokens
Cache write (5 minutes)
¥43.75/M tokens

Additional pricing

Cache write
¥43.75
Cache read
¥3.5
Cache write price 5m
¥43.75
Cache write price 1h
¥70

Specifications

Context
1M
Max output
128K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Google Vertex

Latency
2.9s
Throughput
28 tokens/s
Context
1M

Pricing

Input
¥35/M tokens
Output
¥175/M tokens
Cached
¥3.5/M tokens
Cache write (1 hour)
¥70/M tokens
Cache write (5 minutes)
¥43.75/M tokens

Additional pricing

Cache write
¥43.75
Cache read
¥3.5
Cache write price 5m
¥43.75
Cache write price 1h
¥70

Specifications

Context
1M
Max output
128K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Claude Opus 4.8 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-opus-4.8", 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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