Anthropic

Claude Haiku 5.5

anthropic/claude-haiku-5.5
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Claude Haiku 5.5 是 Anthropic 公司推出的一款小型、高效的模型,适用于需要高吞吐量且注重成本优化的任务,例如摘要生成、子代理服务以及浏览器应用等场景。它在前作 Claude Haiku 4.5 的基础上进行了改进,性能更优越,计算效率更高,更适合知识密集型任务。

Input / output modalities
Not provided to Not provided
Reference input / output price
Input¥0.7Output¥3.5per 1M tokens
Context window
200K
Added to catalog
Oct 8, 2026

Providers and pricing

ProviderInput lengthInput /MOutput /MCached /MContextMax outputDetails
Amazon Bedrock≤ 100K¥0.7¥3.5¥0.07200K64K
> 100K¥3.5¥17.5¥0.35

Amazon Bedrock

Latency
1.07s
Throughput
118 tokens/s
Context
200K

Pricing

Input
¥0.7/M tokens
Output
¥3.5/M tokens
Cached
¥0.07/M tokens

Tiered pricing

Pricing varies by input token range.

0–100K Token

Input tier
¥0.7/M tokens
Output tier
¥3.5/M tokens
Cached tier
¥0.07/M tokens
5-minute cache write tier
¥0.88/M tokens

100K–∞ Token

Input tier
¥3.5/M tokens
Output tier
¥17.5/M tokens
Cached tier
¥0.35/M tokens
5-minute cache write tier
¥4.38/M tokens

Specifications

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

Claude Haiku 5.5 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-haiku-5.5", 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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