claude-opus-4.1

completions

byanthropic

claude-opus-4.1

completions

Published by: anthropicProvider:

anthropic

Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains in multi-file code refactoring, debugging precision, and detail-oriented reasoning. The model supports extended thinking up to 64K tokens and is optimized for tasks involving research, data analysis, and tool-assisted reasoning.

Released

May 22, 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 May 22, 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

Access claude-opus-4.1 through LangDB AI Gateway

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99.9% Uptime

10,000+Monthly Requests

Benchmark Results for claude-opus-4.1

Category Performance Scores:

Academia: Score 60.95 (Top 16% - Rank #56)
Finance: Score 39.30 (Top 46% - Rank #159)
Marketing: Score 53.50 (Top 29% - Rank #101)
Maths: Score 36.30 (Top 47% - Rank #163)
Programming: Score 47.50 (Top 18% - Rank #63)
Science: Score 73.90 (Top 12% - Rank #42)
Writing: Score 53.85 (Top 28% - Rank #97)

Overall Performance: 52.18642857142858 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AIME	56.30	Top 22%	Mathematics
AA Coding Index	47.50	Top 18%	Programming
AAII	42.30	Top 23%	General
AA Math Index	36.30	Top 47%	Mathematics
GPQA	79.60	Top 10%	STEM (Physics, Chemistry, Biology)
HLE	5.90	Top 26%	General Knowledge
LiveCodeBench	54.20	Top 27%	Programming
MATH-500	94.10	Top 20%	Mathematics
MMLU-Pro	86.00	Top 2%	General Knowledge
SciCode	40.90	Top 3%	Scientific

GPQA Score: 79.60 - Graduate-level reasoning benchmark

Model Comparison:

Provider: anthropic

Model Type: completions

Context Size: 200000 tokens

Comparing against 345 models in the database

Performance Analytics for claude-opus-4.1

Usage Statistics (Last 2 Days):

Total Requests: 2 API calls
Average TPS: 43.61 tokens per second
Average Response Time: 4230.60ms
Average Time to First Token: 2380.80ms
Total Cost: $0.02
Average Request Cost: $0.0096

Daily Performance Breakdown:

Date	Requests	TPS	Response Time	TTFT	Cost
9/14/2025	1	64.81	5416.20ms	1716.60ms	$0.02
9/16/2025	1	5.91	3045.00ms	3045.00ms	$0.00

Performance Summary:

Model: claude-opus-4.1 by anthropic

Monitoring Period: 9/13/2025 to 9/20/2025

Average Daily Requests: 1

Peak Daily Requests: 1

Statistics

View Full Statistics

Request Volume

Daily API requests

Performance (TPS)

Tokens per second

43.61 tokens/s

Category Scores

Benchmark Tests

View Other Benchmarks

AIME

56.3

Mathematics

AA Coding Index

47.5

Programming

AAII

42.3

General

AA Math Index

36.3

Mathematics

GPQA

79.6

STEM (Physics, Chemistry, Biology)

HLE

5.9

General Knowledge

LiveCodeBench

54.2

Programming

MATH-500

94.1

Mathematics

MMLU-Pro

86.0

General Knowledge

SciCode

40.9

Scientific

Metric	AIME	AA Coding Index	AAII	AA Math Index	GPQA	HLE	LiveCodeBench	MATH-500	MMLU-Pro	SciCode
Score	56.3	47.5	42.3	36.3	79.6	5.9	54.2	94.1	86.0	40.9

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Code Examples

Integration samples and API usage

Code Samples for claude-opus-4.1

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-4.1",
    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-4.1",
    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-4.1",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: claude-opus-4.1

Provider: anthropic

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

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claude-opus-4.1 by anthropic - AI Model Details, Pricing, and Performance Metrics

claude-opus-4.1

claude-opus-4.1

Access claude-opus-4.1 through LangDB AI Gateway

Statistics

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

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