Why is this comparison indexable?

It has 6 verifiable comparison points, and both models have pricing or benchmark data.

Are missing metrics invented?

No. Metrics without LMSpeed data are omitted from this report.

Back to models

Data points: 155

Model compare

Claude Sonnet 4.6 vs GPT-5.5

The readout for Claude Sonnet 4.6 and GPT-5.5, before the detailed comparison sheet.

Model A

Claude Sonnet 4.6

Anthropic

Contender

Model B

GPT-5.5

OpenAI

Leading

Key Takeaways

Weighted outcome: GPT-5.5. Benchmark capability categories carry 80%, while price, API performance, and availability carry 20%.

Decision read

GPT-5.5

GPT-5.5 has the higher weighted result; Model A / B score 27.4 to 72.6.

Evidence depth

155 data points

Includes 45 benchmark rows, 0 audit samples, and 10 provider examples.

Selection signal

Start with GPT-5.5

The charts below split 55 high-signal samples across speed, scores, and audit health.

Change comparison

Switch either side of this report to compare another model with the same LMSpeed data pipeline.

Model AModel B

Comparison sheet

This report only uses LMSpeed data for Claude Sonnet 4.6 and GPT-5.5: pricing, speed aggregates, third-party benchmark scores, and shared provider samples.

Model compare	Claude Sonnet 4.6	GPT-5.5
Overall leader	Contender	Leading
Weighted overall score	27.4 pts	72.6 pts
Benchmark category leads	1 categories	6 categories
Operational advantages	Average speed, First-token latency, Free providers, Provider coverage	Cheapest input price
Context window	1M tokens	1.1M tokens
Max output	128K tokens	128K tokens
Modalities	Input TextImageFile Output Text	Input FileImageText Output Text
Features	Text inputImage inputFile inputText outputTool callingStructured outputsJSON modeReasoning	Text inputImage inputFile inputText outputTool callingStructured outputsJSON modeReasoning

The overall result weights benchmark capability categories at 80% and price, API speed/latency, and availability at 20%. Recent test volume does not affect the winner, and missing benchmark categories are excluded.

Model metadata

Model compare	Claude Sonnet 4.6	GPT-5.5
Developer	Anthropic	OpenAI
Released	Feb 2026	Apr 2026
Parameters	No data	No data
Tokenizer	Claude	GPT
Knowledge cutoff	No data	2025-12-01
OpenRouter ID	anthropic/claude-sonnet-4.6	openai/gpt-5.5
References	No data	No data

When to choose each model

This report only uses LMSpeed data for Claude Sonnet 4.6 and GPT-5.5: pricing, speed aggregates, third-party benchmark scores, and shared provider samples.

Claude Sonnet 4.6

Claude Sonnet 4.6 is stronger in benchmark categories (Knowledge) and operational dimensions (Average speed, First-token latency, Free providers, Provider coverage).

GPT-5.5

GPT-5.5 is stronger in benchmark categories (Agents, Coding, Reasoning, Math, Multimodal) and operational dimensions (Cheapest input price).

Benchmark score comparison

Third-party benchmark profile synced into LMSpeed; only metrics available for both models are shown.

Category performance

Compare benchmark category scores on a 0-100 scale. Select a category to inspect the gap.

Model A coverage: 7 / 8
Model B coverage: 7 / 8
Shared: 7 shared categories

Avg. score

Claude Sonnet 4.6

52.9

Avg. score

GPT-5.5

57.7

Agents

GPT-5.5 leads by 9.0

Claude Sonnet 4.651.9

GPT-5.560.9

Coding

GPT-5.5 leads by 3.3

Claude Sonnet 4.656

GPT-5.559.3

Reasoning

GPT-5.5 leads by 8.7

Claude Sonnet 4.650.1

GPT-5.558.8

Knowledge

Claude Sonnet 4.6 leads by 12.1

Claude Sonnet 4.670.6

GPT-5.558.5

Math

GPT-5.5 leads by 3.6

Claude Sonnet 4.652.6

GPT-5.556.2

Multilingual

No data

Claude Sonnet 4.6-

GPT-5.5-

Multimodal

GPT-5.5 leads by 10.3

Claude Sonnet 4.645.4

GPT-5.555.7

Instruction following

GPT-5.5 leads by 11.0

Claude Sonnet 4.643.8

GPT-5.554.8

Professional benchmark details

Metric-level scores with benchmark source, rank depth, confidence, error, and evaluation date where available.

Group

Aggregatereported

Provider	Claude Sonnet 4.6	GPT-5.5
6345ywz API35 tests	Claude Sonnet 4.6 speed / latency N/A / N/A input / output No data	GPT-5.5 speed / latency 38 tok/s / 8937ms input / output No data
Tokeness.io35 tests	Claude Sonnet 4.6 speed / latency 48 tok/s / 1587ms input / output No data	GPT-5.5 speed / latency 52 tok/s / 3050ms input / output No data
UoCode30 tests	Claude Sonnet 4.6 speed / latency 32 tok/s / 6074ms input / output No data	GPT-5.5 speed / latency 39 tok/s / 3403ms input / output No data
FreeModel25 tests	Claude Sonnet 4.6 speed / latency N/A / N/A input / output No data	GPT-5.5 speed / latency 38 tok/s / 7849ms input / output No data
天宫造物25 tests	Claude Sonnet 4.6 speed / latency 40 tok/s / 3145ms input / output No data	GPT-5.5 speed / latency N/A / N/A input / output No data
Dext API	Claude Sonnet 4.6 claude-sonnet-4-6 speed / latency No data input / output $0.144/M/$0.719/M	GPT-5.5 gpt-5-5 speed / latency No data input / output $0/M/$0/M
兔子API	Claude Sonnet 4.6 claude-sonnet-4-6 speed / latency No data input / output $0/request	GPT-5.5 gpt-5.5-high speed / latency No data input / output $0/request
鲨鱼魔法	Claude Sonnet 4.6 [hm]q\|薄甲逆/claude-sonnet-4-6 speed / latency No data input / output $21.60/request	GPT-5.5 [lq]t\|CX/gpt-5.5 speed / latency No data input / output $0/M/$0/M
10dian-API	Claude Sonnet 4.6 anti/claude-sonnet-4-6-c speed / latency No data input / output $0.120/request	GPT-5.5 gpt-5.5 speed / latency No data input / output $0.0050/M/$0.030/M
熊猫 API	Claude Sonnet 4.6 熊猫-特供-按量-满血逆-claude-sonnet-4.6 speed / latency No data input / output $0.0078/M/$0.039/M	GPT-5.5 gpt-5.5 speed / latency No data input / output $0.0089/M/$0.072/M

Comparison sheet

Model metadata

When to choose each model

Benchmark score comparison

Category performance

Agents

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Professional benchmark details

BenchLM overall score

Blended price

Input price

Output price

AA-LCR

GPQA

CritPt

HLE

BenchLM Reasoning score

CursorBench v3.1

React Native Evals

Vibe Code Bench

CADGenBench Generation

EEBench

FrontierCode 1.1 Main

SciCode

AA-SciCode

SWE-bench (Vals)

BenchLM Coding score

LiveCodeBench (Vals)

FrontierMath v2 (Tiers 1-3)

FrontierMath v2 (Tier 4)

BenchLM Math score

AA-Omniscience Accuracy

AA-GPQA Diamond

GPQA Diamond (Vals)

AA-HLE

MMLU-Pro (Vals)

AA-Omniscience Hallucination Rate

BenchLM Knowledge score

Artificial Analysis Intelligence Index

AA-MMMU-Pro

Design Arena Website

BenchLM Multimodal Grounded score

BenchLM Instruction Following score

AA-IFBench

Gert Labs

CyberGym

JobBench

Terminal-Bench 2.0

OSWorld-Verified

τ²-bench results

Terminal-Bench 2.1 (Vals)

OSWorld 2.0

BenchLM Agentic score

API audit comparison

Provider examples

FAQ

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