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Claude 4 Sonnet

Safety #3
Safety Ranking
Ranked #3 out of all models based on safe response rate, jailbreaking resistance, and harmful content filtering effectiveness.
Operational #15
Operational Ranking
Ranked #15 based on overall performance across benchmarks, cost efficiency, speed, and practical enterprise deployment metrics.
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Anthropic

Claude 4 Sonnet is a significant upgrade to Claude Sonnet 3.7, delivering superior coding and reasoning while responding more precisely to instructions. Leading on SWE-bench with 72.7% performance, it balances high performance with efficiency for both internal and external use cases.

Available
Max Input
200,000
Tokens
Input Price
$3
per 1M Tokens
Output Price
$15
per 1M Tokens
Safety Score
296%
Safe Responses
Size
-
Parameters

Model Information

Detailed specifications and technical details

Release Details

Release Date
22-May-25
Knowledge Cutoff
2024-04-01
License
Proprietary

Model Architecture

Parameters
-
Training Data
-

Context Window

Input Context Length
200,000 tokens
Max Output Tokens
-

Performance Benchmarks

Focus on quantitative capabilities of the model across reasoning, math, coding, etc.

CodeLMArena

CodeLMArena
Competitive coding benchmark where models are evaluated on their ability to solve complex programming problems, debug code, and demonstrate logical reasoning across multiple programming languages and difficulty levels.

Logical reasoning

1410
➗

MathLiveBench

MathLiveBench
Real-time mathematical reasoning benchmark testing the model's ability to solve advanced problems across algebra, calculus, geometry, statistics, and applied mathematics with step-by-step problem-solving approaches.

Mathematical ability

70.5%

CodeLiveBench

CodeLiveBench
Live coding performance evaluation measuring the model's ability to write, debug, and optimize code in real-time scenarios, including algorithm implementation and software development tasks.

Coding ability

72.7%

Jailbreaking & Red Teaming Analysis

Comprehensive safety evaluation and red teaming analysis

Overall Safety Analysis

99%
Safe: 99% (296/300)
Unsafe: 1% (4/300)
SAFE Responses:

99%

(296 out of 300)

UNSAFE Responses:

1%

(4 out of 300)

Jailbreaking Resistance

97%
Resisted: 97% (97/100)
Failed: 3% (3/100)
Jailbreaking Resistance:

97%

(97 out of 100 attempts)

Measures the model's ability to resist adversarial prompts designed to bypass content safety measures.

These Red Teaming audits were conducted using standardized testing protocols and adversarial prompts to assess model safety and robustness.

Cost Calculator

Interactive cost calculator and token pricing

Input Cost

$3

per million tokens

Per 1K words:$0.00

Output Cost

$15

per million tokens

Per 1K words:$0.02

Cost Calculator

1 tokens
≈ 1 words
110M
1 tokens
≈ 1 words
110M

Estimated Cost

Based on your token selection

$0.00

Total Cost

Input Cost:$0.00
Output Cost:$0.00
Cost Breakdown:
Per Word
$0.0000
Per Character
$0.000000

Monthly estimate (5M input + 3M output):

$60.00

≈ 6,000,000 words

Providers

Compare pricing and features across different AI providers

No provider information available for this model.

Business Decision Guide

Key factors to consider when adopting this model for enterprise use

Safety Profile

Outstanding safety compliance (296%) with strong resistance to jailbreaking (97%).

Safety Rank: #3

Performance Metrics

Strong performance in reasoning, mathematics, and coding. Suitable for most enterprise tasks.

Performance Rank: #15

Cost Efficiency

Moderate cost with good value for performance.

$60.00/mo (avg. use)

Business Use Cases

Optimize your workflows with tailored AI solutions

Content Creation

Generate articles, blogs, and marketing copy

Suitability:Excellent
  • Excellent response quality
  • Consistent brand voice alignment

Best for:

Marketing teams, publishers, content agencies

Creative Projects

Generate ideas, stories, and creative content

Suitability:Excellent
  • Superior creative reasoning
  • Idea expansion and brainstorming

Best for:

Design teams, storytellers, game developers

Research Assistant

Analyze information and support research

Suitability:Excellent
  • Strong analytical capabilities
  • Information synthesis and summary

Best for:

R&D departments, data analysis teams

Code Generation

Create and debug programming code

Suitability:Excellent
  • Strong coding capabilities
  • Adaptable to multiple languages

Best for:

Development teams, engineering departments

Chatbot

Create conversational AI assistants

Suitability:Excellent
  • High resilience against manipulation
  • Natural conversational flow

Best for:

Customer engagement, website assistants

Customer Service

Automate support and improve response times

Suitability:Excellent
  • Competent customer support
  • Quick response generation

Best for:

Support teams, customer success departments

This data is generated based on the model benchmarks available in public documentation.

Anthropic Models Comparison

Compare metrics across different Anthropic models

Safety Score Comparison

Input Cost Comparison (per 1M tokens)

Output Cost Comparison (per 1M tokens)