How much does Anthropic: Claude Opus 4.7 cost on Ofox?

Anthropic: Claude Opus 4.7 on Ofox.ai costs $5/M per million input tokens and $25/M per million output tokens. Pay-as-you-go, no monthly fees.

What is Anthropic: Claude Opus 4.7's context window?

Anthropic: Claude Opus 4.7 supports a context window of 1,000,000 tokens, allowing you to process large documents and maintain long conversations.

How to use Anthropic: Claude Opus 4.7 API via Ofox?

Simply set your base URL to https://api.ofox.io/v1 and use your Ofox API key. The API is OpenAI-compatible — just change the base URL and API key in your existing code.

What capabilities does Anthropic: Claude Opus 4.7 support?

Anthropic: Claude Opus 4.7 supports the following capabilities: vision, function calling, reasoning, prompt caching, pdf input. Access all features through the Ofox.ai unified API.

Anthropic: Claude Opus 4.7

Name: Anthropic: Claude Opus 4.7
Brand: anthropic
Price: 5 USD
Availability: InStock
Rating: 5 (1 reviews)

Chat

anthropic/claude-opus-4.7

比較 Playground で試す始める

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on complex, multi-step tasks and more reliable agentic execution across extended workflows. It is especially effective for asynchronous agent pipelines where tasks unfold over time - large codebases, multi-stage debugging, and end-to-end project orchestration.

コンテキストウィンドウ

最大出力トークン

128K

リリース日

2026-04-16

機能

VisionFunction Calling推論プロンプトキャッシュPDF入力

利用可能なプロバイダー

Bedrock

対応プロトコル

openaianthropic

Providers

Bedrock

入力トークン

$5/M

出力トークン

$25/M

キャッシュ読込

$0.5/M

キャッシュ書込（5分）

$6.25/M

キャッシュ書込（1時間）

$10/M

Web検索

$0.015/R

Protocols

openai/v1/chat/completions/v1/responses

anthropic

コード例

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.ofox.io/anthropic",
    api_key="YOUR_OFOX_API_KEY",
)

message = client.messages.create(
    model="anthropic/claude-opus-4.7",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ],
)

print(message.content[0].text)