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Claude Sonnet 3.7

Chat modelSonnetClaude 3.7

Claude Sonnet 3.7

Release date: 2025-02-25Updated: 2025-02-25Views: 1,476
Live demoGitHubHugging FaceCompare
Parameters
No data
Context length
128K
Multilingual
Supported
Reasoning ability
No data

Claude Sonnet 3.7 is an AI model published by Anthropic, released on 2025-02-25, for Chat model, and 128K context length, with a 82.20 score on MATH-500.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

Claude Sonnet 3.7

Model basics

Reasoning traces
No data
Thinking modes
Thinking modes not supported
Context length
128K tokens
Max output length
No data
Model type
Chat model
Modality (in / out)
No data
Release date
2025-02-25
Model file size
No data
MoE architecture
No
Total params / Active params
No data / Not applicable
Knowledge cutoff
No data
Claude Sonnet 3.7

Open source & experience

Code license
Proprietary
Weights license
Proprietary
GitHub repo
N/A
Hugging Face
N/A
Live demo
N/A
Claude Sonnet 3.7

Official resources

Paper
DataLearnerAI blog
Claude Sonnet 3.7

API details

API speed
No data
💡Default unit: $/1M tokens. If vendors use other units, follow their published pricing.
Standard
TypeConditionInputOutput
Text-$3.00/ 1M$15.00/ 1M
Image-$3.00/ 1M
Batch
TypeConditionInputOutput
Text-$1.50/ 1M$7.50/ 1M
Image-$1.50/ 1M
Cache PricingPrompt Cache
TypeTTLWriteRead
Text-$3.75/ 1M$0.300/ 1M
Text-$3.75/ 1M
Cache = write
Text-$0.300/ 1M
Cache = hit
Image-$3.75/ 1M
Cache = write
Image-$0.300/ 1M
Cache = hit

“—” means the modality is not billed in that direction, or the vendor has not published a price for it.

Claude Sonnet 3.7

Benchmark Results

Claude Sonnet 3.7 currently shows benchmark results led by Aider-Polyglot (18 / 59, score 64.90), SimpleBench (35 / 67, score 46.40), SWE-bench Verified (61 / 114, score 70.30). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.

Thinking
Tool usage

General Knowledge

1 evaluations
Benchmark / mode
Score
Rank/total
HLE
Thinking Mode
10.30
162 / 188

General Evaluation

2 evaluations
Benchmark / mode
Score
Rank/total
GPQA Diamond
Standard Mode
68
204 / 270
GPQA Diamond
Thinking Mode
77
163 / 270

Coding and Software Engineer

3 evaluations
Benchmark / mode
Score
Rank/total
SWE-bench Verified
Standard ModeTools
62.30
80 / 114
SWE-bench Verified
Thinking ModeTools
70.30
61 / 114
GSO
Standard ModeTools
3.80
19 / 21

Math and Reasoning

5 evaluations
Benchmark / mode
Score
Rank/total
MATH-500
Standard Mode
82.20
41 / 44
AIME2025
Standard Mode
54.80
84 / 106
AIME 2024
Standard Mode
23.30
58 / 62
FrontierMath
Standard Mode
3.10
46 / 60
FrontierMath
Thinking Mode
4.10
41 / 60

Common Sense Reasoning

2 evaluations
Benchmark / mode
Score
Rank/total
SimpleBench
Standard Mode
44.90
39 / 67
SimpleBench
Thinking Mode
46.40
35 / 67

Agent Level Benchmark

7 evaluations
Benchmark / mode
Score
Rank/total
Aider-Polyglot
Standard Mode
60.40
21 / 59
64.90
18 / 59
τ²-Bench
Thinking ModeTools
61.80
30 / 43
METR Time Horizons v1.1
Standard ModeTools
60.39
16 / 22
56.09
17 / 22
τ²-Bench - Telecom
Thinking ModeTools
55
31 / 35
Terminal Bench Hard
Thinking ModeTools
21
13 / 13

Productivity Knowledge

1 evaluations
Benchmark / mode
Score
Rank/total
GDPval-AA
Thinking Mode
28
20 / 21

Long Context

1 evaluations
Benchmark / mode
Score
Rank/total
AA-LCR
Thinking Mode
61
26 / 27

AI Agent - Tool Usage

1 evaluations
Benchmark / mode
Score
Rank/total
OSWorld-Verified
Thinking ModeTools
28
26 / 26

Multimodal Understanding

3 evaluations
Benchmark / mode
Score
Rank/total
GeoBench ACW
Standard Mode
68
14 / 20
VPCT
Standard Mode
39
18 / 24
VPCT
64K
35
22 / 24

Long Context

1 evaluations
Benchmark / mode
Score
Rank/total
Fiction.liveBench
Standard Mode
50
16 / 16
Claude Sonnet 3.7

Publisher

Claude Sonnet 3.7

Model Overview

Claude Sonnet 3.7 is an AI model published by Anthropic, released on 2025-02-25, for Chat model, and 128K context length, with a 82.20 score on MATH-500.

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