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claude-opus-4.7 vs gpt-5.5

Compare claude-opus-4.7 from anthropic and gpt-5.5 from openai side by side — pricing, context window, features, and provider availability.

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claude-opus-4.7

claude-opus-4.7

By : anthropic

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.

Beyond coding, Opus 4.7 brings improved knowledge work capabilities - from drafting documents and building presentations to analyzing data. It maintains coherence across very long outputs and extended sessions, making it a strong default for tasks that require persistence, judgment, and follow-through.

gpt-5.5

gpt-5.5

By : openai

GPT‑5.5 understands what you’re trying to do faster and can carry more of the work itself. It excels at writing and debugging code, researching online, analyzing data, creating documents and spreadsheets, operating software, and moving across tools until a task is finished. Instead of carefully managing every step, you can give GPT‑5.5 a messy, multi-part task and trust it to plan, use tools, check its work, navigate through ambiguity, and keep going.

Model Overview

Feature
anthropicclaude-opus-4.7
openaigpt-5.5
Input Context Window
The number of tokens supported by the input context window.
1M
tokens
1.1M
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
128K
tokens
128K
tokens
Release Date
When the model was first released.
April 16, 2026
6 months ago
April 25, 2026
6 months ago
Input Type
The types of inputs the model can process.
Output Type
The types of outputs the model can process.
gpt-5.5 offers a larger context window (1,050,000 tokens vs 1,000,000 tokens). claude-opus-4.7 is cheaper for output tokens ($25/M vs $30/M). claude-opus-4.7 has lower latency (932ms vs 3286ms). gpt-5.5 achieves higher throughput (84 tok/s vs 6 tok/s). claude-opus-4.7 supports reasoning capabilities, while gpt-5.5 does not.

Providers for Claude Opus 4.7

OpenQiao Provider to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

AnthropicAnthropic
Status
Latency
-
Throughput
-
Uptime
-
Price
Input
$ 5/ M tokens
Output
$ 25/ M tokens
Cache read
$ 0.5/ M tokens
Cache write 5m
$ 6.25/ M tokens
Cache write 1h
$ 10/ M tokens
Cache write
-
Web search
$ 0.01/ counts
Image
-
Image input
-
Image output
-
Image cache
-
reasoning
-
Video
-
Audio
-
Audio cache read
-
Audio input
-
Audio & Video
-
Image search
-
Web search image
-
Status Page

Providers for GPT-5.5

OpenQiao Provider to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

OpenAIOpenAI
Status
Latency
-
Throughput
-
Uptime
-
Price
Input
$ 5/ M tokens
Output
$ 30/ M tokens
Cache read
$ 0.5/ M tokens
Cache write 5m
-
Cache write 1h
-
Cache write
-
Web search
$ 0.01/ counts
Image
-
Image input
gpt-image-2.5-sunburst
$ 8/ M tokens
Image output
gpt-image-1
$ 40/ M tokens
Image cache
gpt-image-2.5-sunburst
$ 2/ M tokens
reasoning
-
Video
-
Audio
-
Audio cache read
-
Audio input
-
Audio & Video
-
Image search
-
Web search image
-
Status Page

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How to use claude-opus-4.7 or gpt-5.5

Simply change the model name to claude-opus-4.7 or gpt-5.5 to adjust the model. OpenQiao normalizes requests and responses across providers for you.

from openai import OpenAI

client = OpenAI(
  base_url="https://openqiao.com/api/v1",
  api_key="<OPENQIAO_API_KEY>",
)

# Chat Completion
completion = client.chat.completions.create(
  model="claude-opus-4.7",
  messages=[
    {
      "role": "user",
      "content": "What is the meaning of life?"
    }
  ]
)
print(completion.choices[0].message.content)

# Responses API
responses = client.responses.create(
  model="claude-opus-4.7",
  input="What is the meaning of life?"
)
print(responses)

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