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AI model reference · 2026

Claude Sonnet 4.5

Anthropic: Claude Sonnet 4.5 logoAnthropicModel details, evidence, and API facts

Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows.

Text generation
Image input
Reasoning
Provider endpoint accepts tool parameters
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Context window
1,000,000 tokens
Maximum output
64,000 tokens
Base provider API input
$3.00 / 1M tokens
Starting provider API rate; context tiers apply
Published evidence
3 benchmarks, 0 Arena results

Overview

About Claude Sonnet 4.5

A concise catalog overview. Technical limits and published evaluation evidence are listed separately below.

Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows.

text
multimodal
reasoning

Published evaluations

Benchmark results

Only results mapped to this exact model and backed by a named source appear here. Different evaluation protocols are not treated as interchangeable.

Source-backed benchmark results for Claude Sonnet 4.5
BenchmarkScoreEvaluation detailsSource
OSWorld-VerifiedA verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.62.9%Mean task rewardVersion: OSWorld-Verified v1 · Split: Up to 361 tasks, excluding eight Google Drive tasks where required · Harness: Official OSWorld unified environment · Attempts: One run · Tools: GUI interactionProtocol note: Only 100-step general-model rows are included in this normalized snapshot. Individual evaluated-task counts can differ when a task could not run.; Run date: 2025-10-30; Evaluated tasks: 360Methodology OSWorldBenchmark owner
SWE-Bench VerifiedA human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.71.4%ResolvedVersion: SWE-Bench Verified 500 · Split: Verified, 500 tasks · Harness: mini-SWE-agent / version 2.0.0 · Attempts: One attempt · Reasoning effort: highProtocol note: Harness version: 2.0.0; Run date: 2026-02-17Methodology SWE-benchBenchmark owner
Vending-Bench 2Tests AI models ability to manage a simulated vending machine business over a year3,838.74Money Balance ($)The published protocol is not fully disclosed.Methodology andonlabs.comLegacy leaderboard

Human preference

Arena results

Arena scores come from blind human preference votes. They are reported separately from task benchmarks and are not used as substitutes for missing benchmark results.

No exact Arena match is available for this model. Similar names and provider variants are not merged automatically.

Technical reference

Specifications and API facts

Technical limits and reference provider prices come from the current catalog unless a reviewed external source is listed. Missing values stay marked as unavailable.

Model
Provider
Anthropic
Release date
Not available in reviewed sources
Catalog added
Sep 29, 2025
Context window
1,000,000 tokens
Maximum output
64,000 tokens
Knowledge cutoff
2025-01-31
License
Not available in reviewed sources
Capabilities and API
Input types
Text, Image, File
Output types
Text
Reasoning
Supported
Provider endpoint tool parameters
Accepts tool parameters
Base provider API input
$3.00 / 1M tokens
Base provider cached input
$0.30 / 1M tokens
Base provider API output
$15 / 1M tokens
Provider tier at ≥ 200,000 prompt tokens
Input $6.00 / 1M tokensOutput $22.5 / 1M tokensCached input $0.60 / 1M tokens

Provider token rates are context-dependent. The base rates apply below the listed prompt thresholds; the matching tier applies at or above each threshold.

These are reference provider API rates, not Writingmate checkout charges. Access in Writingmate follows the allowances of your Writingmate plan.

Provenance

Sources and update status

Source links are attached to the facts and evaluations they support. Catalog-only values are not presented as independently verified claims.

Evidence last updated Aug 9, 2026.

Catalog record updated Sep 29, 2025.

Catalog-added dates describe when a model entered the catalog, not necessarily its public release date.

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