Moduck

Anthropic: Claude Opus 4.7

Stronger Opus tier for advanced software work and high-stakes reasoning

Model lab
Anthropic
Model family
claude-opus
Modalitiestext, image, pdf → text
Context window1,000,000
Maximum output128,000
InputUSD 4 / 1M tokens
OutputUSD 20 / 1M tokens

Quickstart

Use your Moduck API Key, set the API base URL to https://api.moduck.ai/v1, and set the model parameter to anthropic/claude-opus-4-7.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "anthropic/claude-opus-4-7"

response = requests.post(
    f"{base_url}/chat/completions",
    headers={
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    },
    json={
        "model": model_id,
        "messages": [{"role": "user", "content": "Hello!"}],
        "stream": False,
    },
    timeout=60,
)
response.raise_for_status()
print(response.json())

Use the familiar OpenAI-style chat request format to make model integration easier.

Claude Opus 4.7 API Pricing

TypePrice information
InputUSD 4 / 1M tokens
OutputUSD 20 / 1M tokens

Benchmarks

Max

Intelligence Index · v4.340.7
Coding Index73.6
Agentic Index38.6
BenchmarkScoreMeasurementSource
SWE-Bench Pro64.3resolve rate · Date: 2026-05-28
Terminal-Bench66.1success rate · Harness: Terminus-2 · Version: 2.1 · Date: 2026-05-28
SWE-Atlas Refactoring48.57score · Harness: Claude Code
Artificial Analysis Coding Agent Index66.6average pass@1 · Variant: max · Harness: Claude Code
SWE-Atlas Codebase QnA81pass@1 · Variant: max · Harness: Claude Code
SWE-Bench Pro44.9pass@1 · Dataset: hard-aa · Variant: max · Harness: Claude Code
Terminal-Bench73.8pass@1 · Variant: max · Harness: Claude Code · Version: 2.1
Artificial Analysis Coding Agent Index61.2average pass@1 · Variant: medium · Harness: Cursor CLI
SWE-Atlas Codebase QnA78.4pass@1 · Variant: medium · Harness: Cursor CLI
SWE-Bench Pro34.4pass@1 · Dataset: hard-aa · Variant: medium · Harness: Cursor CLI
Terminal-Bench70.6pass@1 · Variant: medium · Harness: Cursor CLI · Version: 2.1
Artificial Analysis Coding Agent Index59.9average pass@1 · Variant: medium · Harness: Claude Code
SWE-Atlas Codebase QnA71.7pass@1 · Variant: medium · Harness: Claude Code
SWE-Bench Pro36.4pass@1 · Dataset: hard-aa · Variant: medium · Harness: Claude Code
Terminal-Bench71.4pass@1 · Variant: medium · Harness: Claude Code · Version: 2.1
GPQA Diamond94.2accuracy · Date: 2026-04-23
Humanity's Last Exam46.9accuracy · Variant: no tools · Date: 2026-04-23
Humanity's Last Exam54.7accuracy · Variant: with tools · Date: 2026-04-23
OSWorld-Verified78success rate · Date: 2026-04-23

Performance

Measured on the Moduck gateway across live traffic, hour by hour over the last 24 hours. Time to first token is how long before anything appears; throughput is how fast the answer is written after that; end-to-end latency is the whole round trip. Figures are medians unless the card says otherwise.

Artificial Analysis measurement · Max

Output speed52.34 tokens/s
Time to first token20.07 s
Time to first answer token—
End-to-end response time—
Measurement variantOutput speedTime to first tokenTime to first answer tokenEnd-to-end response time
Max52.34 tokens/s20.07 s——

Performance trends

Throughput52.34 tok/sCurrent
Time to first token20.07 sCurrent
End-to-end latency7.6 sCurrent
Throughput
Current52.34 tok/s
Window average51.7 tok/s
Time to first token
Current20.07 s
Window average20.6 s
End-to-end latency
Current7.6 s
Window average7.5 s
Tail latency (P99)
Current16.5 s
Window average16.9 s
Prompt cache hit rate
Current26.3%
Window average23.3%
Error rate
Current0.0%
Window average0.2%

Availability

Uptime is the share of time at least one provider serving this model responded. Availability is stricter: the share of requests actually served. A provider that answers but fails part of the traffic lowers availability without lowering uptime. Both cover the last three days.

Uptime100%At least one provider responded
Availability100%Requests actually served
Error rate0%Share of failed requests
Served requests, hour by hour
24 hours agoNow

Claude Opus 4.7 Compare models

ModelInput priceOutput priceContext windowCapabilities
Claude Opus 4.7This pageUSD 4 / 1M tokensUSD 20 / 1M tokens1,000,000Text output · Reasoning · Tool calling
Claude Opus 5.5USD 3.2 / 1M tokensUSD 16 / 1M tokens1,000,000Text output · Reasoning · Tool calling
Claude Opus 5USD 4 / 1M tokensUSD 20 / 1M tokens1,000,000Text output · Reasoning · Tool calling
Claude Opus 4.8USD 3.43432 / 1M tokensUSD 17.17168 / 1M tokens1,000,000Text output · Reasoning · Tool calling
Claude Opus 4.6USD 4 / 1M tokensUSD 20 / 1M tokens1,000,000Text output · Reasoning · Tool calling

Model specifications

Input
text, image, pdf
Output
text
Context window
1,000,000
Maximum output
128,000
Release date
2026-04-16
Attachments
Yes
Reasoning
Yes
Tool calling
Yes
Temperature setting
No
Open weights
No

Frequently asked questions

What is Claude Opus 4.7 for?

Stronger Opus tier for advanced software work and high-stakes reasoning

What inputs and outputs does Claude Opus 4.7 support?

Recorded inputs: text, images, PDF; outputs: text.

How is Claude Opus 4.7 priced?

The pricing table shows the current recorded Moduck price. For example: Input USD 4 / 1M tokens; Output USD 20 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for Claude Opus 4.7?

Current model records list Context window 1,000,000 tokens; Maximum output 128,000 tokens.

What model parameter does the Quickstart use?

The example uses anthropic/claude-opus-4-7. This value comes from the page identifier and is not confirmed as a callable Moduck public ID.

Can I call this model through the Moduck API now?

This page has no verified Moduck API call for this model. A Quickstart example or reserved ID does not establish access; check the models available to your account.