All Models
AnthropicCodeProprietary Commercial APIReleased: 2025-05-22

Claude Sonnet 4

Claude Sonnet 4 is Anthropic's premier balanced engineering model for the Claude 4 generation, engineered for rapid autonomous coding agents, multi-step tool execution, and cost-effective enterprise workflows.

Foundation DNA84/100
HYBRID-REASONING ArchProprietary params
At a Glance Specifications
Context Window

200k

~150k words input

Token Pricing

$3 / $15

Prompt / Completion per 1M

Top Benchmark

73.5 % resolved

SWE-bench Verified

Hardware Tier

Cloud Managed

Zero local VRAM

6-Axis Foundation Model DNA

Holistic Capability Distribution

Normalized 0-100 rating vectors balanced across intelligence, throughput, and economics.

Overall Index:84/100
ReasoningCodingSpeedEconomicsContextFlexibility
Context: 88/100 (Window Horizon)
ReasoningGPQA / Logic / Math
93/100
CodingSWE-bench / LCB
96/100
SpeedTokens / Second
76/100
EconomicsCost Efficiency
82/100
ContextWindow Horizon
88/100
FlexibilityTool Use & Open
90/100
Performance Evaluations

Verified LLM Benchmarks

Empirical evaluations across academic reasoning, software engineering, agentic execution, and human preference.

SWE-bench Verified Headline
73.5% resolved
swebench.harness
CodingAnthropic Claude 4 Announcement
GPQA Diamond Headline
80.5% pass@1
Inspect
Academic ReasoningAnthropic Claude 4 Announcement
Chatbot Arena Elo Headline
1410Elo
LMSYS Blind Pairwise Battles
Human Preferencehttps://chat.lmsys.org/
MATH-500 Headline
96.8% pass@1
lm-eval-harness
MathematicsAnthropic Claude 4 Announcement
Berkeley Function Calling (BFCL v3) Headline
90.5% AST match
BFCL-eval
Agentic ExecutionBerkeley Function Calling Leaderboard v3
LiveCodeBench
71.2% pass@1
lm-eval-harness
CodingAnthropic Claude 4 Announcement
Real-Time Provider Telemetry

Inference Latency & Generation Throughput

Empirical telemetry benchmarking generation throughput (Tokens/Second) and Time to First Token (TTFT).

Peak Generation Speed
80tokens/sec

Measured under concurrent production load

Lowest Time to First Token
420ms

p95 latency: 1200 ms

Telemetry Verification
99.9%uptime

Across 2,400 monitored requests

Production Trade-Offs

Architectural Strengths vs. Operational Considerations

An objective technical balance sheet analyzing deployment advantages and production constraints.

Operational Advantages

Key Architectural Strengths

  • Industry gold standard for automated GitHub issue solving, feature authoring, and test generation.
  • Superb price-to-performance ratio ($3 / $15) with prompt cache reads down to $0.30 per million tokens.
  • High-throughput token emission (80 tps peak) for interactive developer tooling and live completions.
Production Constraints

Operational Considerations

  • Deep multi-step mathematical theorem derivation is best delegated to Opus 4.
Technical Specifications

Hardware & Execution Parameters

Architecture Typehybrid-reasoning
Total ParametersProprietary
Attention MechanismMHA
Context Window200,000 tokens
Max Output Tokens64,000 tokens
Supported Modalities
textimagepdf
License Typeproprietary
Commercial Use Allowed
Model DistillationProhibited
Zero Data RetentionAvailable
Knowledge Cutoff2025-03
Model Heritage & Evolutionary Lineage

Genealogical Provenance

Direct successor to Claude Sonnet 3.7, delivering higher agentic accuracy and reduced latency.

Base Precursor

anthropic claude 3 7 sonnet 20250219

Current Architecture

Claude Sonnet 4

anthropic claude 4 opus 202505
Engineering Deep-Dive

Architecture Engineering & Capability Deep-Dive

Topology & Attention Mechanics

Engineered as an enterprise engineering backbone, Claude Sonnet 4 optimizes instruction execution, repository context comprehension, and multi-turn debugging loops.

Evaluation Profile & Reasoning Capabilities

Offers adaptive test-time compute with fast token delivery when thinking is unneeded, and deep chain-of-thought when requested.

Inference Economics & Cost Optimization

Optimized for continuous CI/CD integration, with 50% batch discounts and $0.30 cache reads.

Primary Production Workloads & Suitability

Repository-level coding agents (Claude Code, Cursor, Cline)
Automated unit and integration test generation
Customer workflow orchestration with tool use
Structured data extraction from messy multi-page documents
Compute & Deployment Architecture

Cloud Deployment Architecture & Hardware Sizing

Cloud Deployment Architecture

Distributed enterprise serving infrastructure, autoscaling semantics, and runtime execution profile.

Cloud APIZero Local VRAM Required

Proprietary commercial model hosted on managed multi-region clusters with automatic autoscaling, high availability, and prompt prefix caching.

SLA: 99.9% Cloud Availability
Rate Limit: Scaled via Provider Quota
Cache: Automatic Prefix Compression
Serving Model

Multi-Tenant Cloud API

Continuous autoscaling with regional failover

Hardware Overhead

0 GB Local VRAM

Inference executed on hyperscaler accelerator clusters

Context Capacity

200k tokens

Supported with automated KV cache prefix compression

SDK Installation

$npm install @anthropic-ai/sdk
$pip install anthropic
Inference Economics & Total Cost of Ownership

Commercial Token Rates & Cost Estimator

Base Input Tokens

$3.00 / 1M

Standard prompt context ingestion

Base Output Tokens

$15.00 / 1M

Generated completion & thinking tokens

Prompt Cache ReadUp to 80% Off

$0.30 / 1M

Re-used prompt prefix context

Monthly Production Cost Simulator

Daily Prompt Ingestion5M tokens/day (~150M/mo)
Daily Completion Generation1M tokens/day (~30M/mo)
Prompt Prefix Cache Hit Rate40%
Estimated Monthly Spend

$738.00

Includes prompt caching

Monthly Cache Savings

-$162.00

Saved via prefix context caching

Frontier Alternatives

Comparable Foundation Architectures

Alternative foundation models with comparable intelligence benchmarks, context windows, and deployment profiles.

AnthropicReasoning

Claude Opus 4

Claude Opus 4 is Anthropic's flagship frontier reasoning model for the Claude 4 generation, featuring an advanced hybrid test-time reasoning engine, 200k context window, and breakthrough scores on graduate-level STEM and multi-step deduction.

Context:200k ctx
Parameters:Proprietary
Input Rate:$15/1M
Compare Architecture
OpenAIMultimodal

GPT-4o

OpenAI's flagship omni model natively processing text, audio, and vision with low-latency multimodal reasoning and a 128,000 token context window.

Context:128k ctx
Parameters:Proprietary
Input Rate:$2.5/1M
Compare Architecture
AnthropicCode

Claude Sonnet 3.7

Claude Sonnet 3.7 is a hybrid reasoning and code model from Anthropic with a 200,000-token context window, supporting text, image, and PDF modalities with dynamic test-time compute control.

Context:200k ctx
Parameters:Proprietary
Input Rate:$3/1M
Compare Architecture
GoogleMultimodal

Gemini 2.0 Flash

Google's next-generation multimodal model built for the agentic era with sub-second latency, native tool use, and a 1,000,000 token context window.

Context:1,048.576k ctx
Parameters:Proprietary
Input Rate:$0.1/1M
Compare Architecture
Developer Quickstart

SDK Installation & API Integration

$npm install @anthropic-ai/sdk
$pip install anthropic
import Anthropic from '@anthropic-ai/sdk';

const anthropic = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY,
});

const response = await anthropic.messages.create({
  model: 'claude-4-sonnet-20250522',
  max_tokens: 4096,
  messages: [
    { role: 'user', content: 'Refactor our Prisma schema to use UUID v7 keys.' }
  ],
});

console.log(response.content);
Knowledge Base

Frequently Asked Questions about Claude Sonnet 4

Engineering specifications, VRAM sizing, commercial licensing terms, token economics, and empirical benchmark evaluations.

Topic:

Its 73.5% SWE-bench Verified score combined with low latency and aggressive prompt caching pricing ($0.30/1M cache read) makes it the benchmark model for autonomous developer loops.

Verified Engineering FAQ

Yes, Anthropic Computer Use API is natively supported with improved screen coordinate precision.

Verified Engineering FAQ
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