SSyncDev

AI model comparison

Claude Sonnet 3.7 vs GPT-5.5

Compare recorded price, context, output limits, speed, latency, capabilities, and input/output support. Every missing value stays visible, and unsourced benchmarks are excluded.

Claude Sonnet 3.7 and GPT-5.5 both come up when teams are choosing a model for production work, and the honest answer usually depends on your workload rather than a leaderboard. This page puts their published specifications side by side — context window, token pricing, supported inputs and outputs — so you can see where they actually differ.

Side-by-sideReviewed by our team

Anthropic

Claude Sonnet 3.7

Balanced Claude model for coding, analysis, agent workflows, and cost control

Context
200K
Max output
64K
Input / 1M
$3.00
Output / 1M
$15.00
Output speed
—

Accepts

  • Text input
  • Image input
  • PDF input

Produces

  • Text output
Full model profileVendor docs ↗
VS

OpenAI

GPT-5.5

Default frontier GPT for coding, computer use, research, and knowledge work

Context
1.1M
Max output
128K
Input / 1M
$5.00
Output / 1M
$30.00
Output speed
—

Accepts

  • Text input
  • Image input
  • PDF input

Produces

  • Text output
Full model profileVendor docs ↗

At a glance

Decision snapshot

This is a directional summary of the values recorded in this directory—not a universal quality verdict. Test the finalists on your own prompts before committing.

Where Claude Sonnet 3.7 leads in recorded data

  • Input price: $3.00
  • Output price: $15.00

Where GPT-5.5 leads in recorded data

  • Context capacity: 1.1M
  • Maximum output: 128K

Context capacity

Higher listed limit

Claude Sonnet 3.7:200K

GPT-5.5:1.1M

GPT-5.5

Maximum output

Higher listed limit

Claude Sonnet 3.7:64K

GPT-5.5:128K

GPT-5.5

Input price

Lower recorded price

Claude Sonnet 3.7:$3.00

GPT-5.5:$5.00

Claude Sonnet 3.7

Output price

Lower recorded price

Claude Sonnet 3.7:$15.00

GPT-5.5:$30.00

Claude Sonnet 3.7

Output speed

Higher recorded throughput

Claude Sonnet 3.7:—

GPT-5.5:—

No complete comparison

Time to first token

Lower recorded latency

Claude Sonnet 3.7:—

GPT-5.5:—

No complete comparison

Intelligence Index

Higher directory index

Claude Sonnet 3.7:—

GPT-5.5:—

No complete comparison

Evidence

Verified shared benchmarks

A score appears only when both records include a verified source. It is not treated as a universal ranking.

These two models haven't been measured on the same benchmark yet, so there's nothing meaningful to chart. Comparing scores from different tests would tell you more about the tests than the models — the specs and pricing above are the better guide here.

Specifications

Pricing, limits and capabilities

SpecificationClaude Sonnet 3.7GPT-5.5
ProviderAnthropicOpenAI
Model familyclaude-sonnetgpt
Accepted inputstext, image, pdftext, image, pdf
Produced outputstexttext
Context window200K1.1MRecorded lead
Max output64K128KRecorded lead
Intelligence Index——
Input price / 1M$3.00Recorded lead$5.00
Output price / 1M$15.00Recorded lead$30.00
Output speed——
Time to first token——
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputNot documentedNot documented
Structured outputNot documentedDocumented
LicenseProprietaryProprietary
ReleasedFeb 19, 2025Apr 23, 2026

Workload guidance

Which model should you choose?

On the published numbers, GPT-5.5 accepts the larger context window and Claude Sonnet 3.7 is cheaper per input token. Which matters more depends on whether your bottleneck is document size or spend — the table above has the exact figures.

Provenance

Sources and data limits

Prices and hosted performance can change. SyncDev records source references and clearly separates documented specifications from measured values; confirm commercial terms with the provider before deployment.

Questions people ask

It compares recorded context and output limits, token prices, output speed, time to first token, Intelligence Index, modality support, tool and structured-output capabilities, release information, and only source-linked benchmarks verified on both records. Missing information is labeled rather than inferred.

Compare a different pair

Choose any two approved model records and review them with the same evidence rules.

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