claude-opus-4

completions

byanthropic

claude-opus-4

completions

Published by: anthropicProvider:

anthropic

Our most capable and intelligent model yet. Claude Opus 4 sets new standards in complex reasoning and advanced coding

Released

Aug 5, 2025

Knowledge

Mar 1, 2025

License

Proprietary

Context

200K

Input

$15 / 1M tokens

Output

$75 / 1M tokens

Cached

$1.5 / 1M tokens

Cached Write

$18.75 / 1M tokens

Capabilities: tools

Accepts: text, image

Returns: text

Released Aug 5, 2025Knowledge Cutoff: Mar 1, 2025License: Proprietary

Context: 200K Input: $15 / 1M tokensOutput: $75 / 1M tokensCached: $1.5 / 1M tokensCached Write: $18.75 / 1M tokensCapabilities: toolsAccepts: text, imageReturns: text

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Benchmark Results for claude-opus-4

Category Performance Scores:

Academia: Score 64.95 (Top 12% - Rank #42)
Marketing: Score 49.00 (Top 21% - Rank #73)
Science: Score 80.90 (Top 10% - Rank #35)
Writing: Score 68.14 (Top 1% - Rank #4)

Overall Performance: 65.7475 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AAII	49.00	Top 14%	General
GPQA	80.90	Top 10%	STEM (Physics, Chemistry, Biology)

GPQA Score: 80.90 - Graduate-level reasoning benchmark

Model Comparison:

Provider: anthropic

Model Type: completions

Context Size: 200000 tokens

Comparing against 347 models in the database

Category Scores

academia#12 marketing#19 science#12 writing#2

Benchmark Tests

View Other Benchmarks

AAII

49.0

General

GPQA

80.9

STEM (Physics, Chemistry, Biology)

Metric	AAII	GPQA
Score	49.0	80.9

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Code Examples

Integration samples and API usage

Code Samples for claude-opus-4

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="claude-opus-4",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "claude-opus-4",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

console.log(response.choices[0].message.content);

cURL Example:

curl -X POST "https://api.us-east-1.langdb.ai/projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: claude-opus-4

Provider: anthropic

API Endpoint: $https://api.us-east-1.langdb.ai

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