Noometry

Model comparison

Claude Opus 4.7 vs GPT-3.5-turbo

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 23.2 on the Noometry Index. GPT-3.5-turbo costs 13× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

Last verified . 28 shared benchmarks.

Claude Opus 4.7 Anthropic

58.3

Rank #19 Confirmed

GPT-3.5-turbo OpenAI

23.2

Rank #350 Confirmed

Summary

  • They share 28 benchmarks with published results for both. Claude Opus 4.7 scores higher in 8 categories and GPT-3.5-turbo in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Claude Opus 4.7 leads 66.7 to 6.3.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 97.8% for Claude Opus 4.7 and 2.2% for GPT-3.5-turbo.
  • GPT-3.5-turbo is cheaper at $0.50 / $1.50 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
  • Claude Opus 4.7 accepts more context: 1M tokens versus 16K.

Side by side

Claude Opus 4.7GPT-3.5-turbo
ProviderAnthropicOpenAI
Noometry Index58.323.2
Released2026-04-142023-03-01
WeightsProprietaryProprietary
Context window1M16K
Max output128K4K
Input $ / M tokens$5$0.50
Output $ / M tokens$25$1.50
Results tracked6644

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Category by category

Coding Claude Opus 4.7 leads

Claude Opus 4.7: 59.6 (#13), GPT-3.5-turbo: 23.9 (#331)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
WeirdML76.4%3.5%
LMArena Coding15181136
SWE-bench Verified83.5%—
FrontierCode38.5%—
LMArena WebDev1558—
SciCode54.5%—
GSO44.1%—
BigCodeBench Instruct—39.1%
MirrorCode31.1%—
BigCodeBench Complete—50.6%
ALE-Bench1,323—
HumanEval+—70.7%
MBPP+—69.7%

Agentic & Tool Use Not comparable

Claude Opus 4.7: 47.9 (#10), GPT-3.5-turbo: —

BenchmarkClaude Opus 4.7GPT-3.5-turbo
Terminal-Bench80.2%—
APEX-Agents49.2%—
OSWorld 2.018.2%—
τ²-bench Banking40.2%—
PostTrainBench28.6%—
ExploitBench26.5%—
GBAEval43.8%—
GDP.pdf21%—
LMArena Search1233—
METR Time Horizons—21.5%
Vending-Bench 210,937—

Reasoning Claude Opus 4.7 leads

Claude Opus 4.7: 53.8 (#29), GPT-3.5-turbo: 13.8 (#332)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
Chess Puzzles30%0%
LMArena Hard Prompts15061108
Mystery Game Puzzles28%3%
DTBench94.7%48.5%
LMCA52.2%9.7%
Epoch Capabilities Index156.25118.55
ForecastBench60.350.4
ARC-AGI-275.8%—
SimpleBench61.7%—
Kagi LLM Benchmark80.7%—
NYT Connections (extended)39%—
ARC-AGI-193.5%—
CritPt12%—
Thematic Generalization72.8%—
EBR-Bench19%—
Adversarial NLI—58.1%
BIG-Bench Hard—61.6%
CommonsenseQA 2.0—57%
WinoGrande—81.6%

Math Claude Opus 4.7 leads

Claude Opus 4.7: 66.7 (#26), GPT-3.5-turbo: 6.3 (#327)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
FrontierMath (Tiers 1-3)70.2%0%
OTIS Mock AIME 2024-202597.8%2.2%
LMArena Math14991142
FrontierMath Tier 431.7%—
MathArena Final-Answer Competitions73.6%—
ProofBench54%—
MATH Level 5—15.9%
FrontierMath (Feb 2025 set)43.8%—
FrontierMath Tier 4 (v1)22.9%—
GSM8K—57.8%

Knowledge Claude Opus 4.7 leads

Claude Opus 4.7: 62.6 (#23), GPT-3.5-turbo: 10.0 (#303)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
GPQA Diamond90.2%28%
LMArena Expert15211070
Humanity's Last Exam36.2%—
SimpleQA Verified51.7%—
Vectara Hallucination Rate12%—
ARC (AI2) Challenge—87.4%
BoolQ—87%
MMLU—71.4%
OpenBookQA—86%
TriviaQA—85.8%

Multimodal Not comparable

Claude Opus 4.7: 41.2 (#38), GPT-3.5-turbo: —

BenchmarkClaude Opus 4.7GPT-3.5-turbo
LMArena Vision1316—
Blueprint-Bench 224.5%—
Furniture Assembly33.3%—
LMArena Document1495—

Multilingual Claude Opus 4.7 leads

Claude Opus 4.7: 57.3 (#10), GPT-3.5-turbo: 31.5 (#258)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
LMArena Non-English14801108
LMArena Chinese15311075
LMArena French15031118
LMArena German14951090
LMArena Japanese14721043
LMArena Korean14641019
LMArena Russian14941123
LMArena Spanish14951121

Instruction Following Claude Opus 4.7 leads

Claude Opus 4.7: 78.4 (#10), GPT-3.5-turbo: 57.9 (#262)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
LMArena Instruction Following14981119

Long Context Claude Opus 4.7 leads

Claude Opus 4.7: 46.2 (#25), GPT-3.5-turbo: 34.0 (#254)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
LMArena Longer Query15051121

Writing & Preference Claude Opus 4.7 leads

Claude Opus 4.7: 75.1 (#8), GPT-3.5-turbo: 25.3 (#305)

BenchmarkClaude Opus 4.7GPT-3.5-turbo
LMArena Text14901125
LMArena Creative Writing14861092
EQ-Bench Creative Writing1914451
LMArena Multi-Turn15051117
EQ-Bench 41311—

Frequently asked questions

Is Claude Opus 4.7 better than GPT-3.5-turbo?

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 23.2 on the Noometry Index. GPT-3.5-turbo costs 13× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4.7 or GPT-3.5-turbo?

GPT-3.5-turbo is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

Is Claude Opus 4.7 or GPT-3.5-turbo better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 23.9 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 16K.

How many benchmarks do Claude Opus 4.7 and GPT-3.5-turbo share?

28 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and GPT-3.5-turbo has 44.

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