Model comparison

GPT-4V vs GPT-5.2

GPT-5.2 has enough public results to be ranked (#34); GPT-4V does not yet, so treat this comparison as directional.

Last verified . 0 shared benchmarks.

GPT-4V OpenAI

36.4

Unranked Sparse

GPT-5.2 OpenAI

54.1

Rank #34 Confirmed

Summary

  • The widest gap is in multimodal, where GPT-5.2 leads 51.3 to 33.2.

Side by side

GPT-4V and GPT-5.2 specifications
GPT-4VGPT-5.2
ProviderOpenAIOpenAI
Noometry Index36.454.1
Released2023-11-062025-12-11
WeightsProprietaryProprietary
Context window—400K
Max output—128K
Input $ / M tokens—$1.75
Output $ / M tokens—$14
Results tracked167

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Category by category

Coding Not comparable

GPT-4V: —, GPT-5.2: 51.6 (#37)

Coding benchmarks
BenchmarkGPT-4VGPT-5.2
SWE-bench Verified—73.8%
SWE-bench Verified (bash only)—72.8%
LMArena WebDev—1416
SWE-bench Multilingual—66.7%
GSO—27.4%
WeirdML—72.2%
LMArena Coding—1447
ALE-Bench—1,294
AlgoTune—2.05

Agentic & Tool Use Not comparable

GPT-4V: —, GPT-5.2: 40.2 (#24)

Agentic & Tool Use benchmarks
BenchmarkGPT-4VGPT-5.2
Terminal-Bench—64.9%
Berkeley Function Calling Leaderboard—55.9%
GDPval—49.7%
Remote Labor Index—2.5%
τ²-bench Airline—83%
τ²-bench Banking—32.2%
τ²-bench Retail—81.6%
τ²-bench Telecom—89.7%
DeepResearch Bench—41.1%
LMArena Search—1207
METR Time Horizons—75.3%
Vending-Bench 2—3,591

Reasoning Not comparable

GPT-4V: —, GPT-5.2: 50.2 (#35)

Reasoning benchmarks
BenchmarkGPT-4VGPT-5.2
ARC-AGI-2—52.9%
SimpleBench—45.8%
Kagi LLM Benchmark—73.3%
NYT Connections (extended)—83.6%
ARC-AGI-1—86.2%
Chess Puzzles—49%
EnigmaEval—10.4%
EBR-Bench—23%
LMArena Hard Prompts—1445
Mystery Game Puzzles—23%
DTBench—90.9%
LMCA—43.9%
Epoch Capabilities Index—153.45
ForecastBench—60.1

Math Not comparable

GPT-4V: —, GPT-5.2: 60.0 (#38)

Knowledge Not comparable

GPT-4V: —, GPT-5.2: 59.3 (#32)

Knowledge benchmarks
BenchmarkGPT-4VGPT-5.2
GPQA Diamond—91.4%
Humanity's Last Exam—27.8%
SimpleQA Verified—37.1%
Vectara Hallucination Rate—8.4%
LMArena Expert—1445

Multimodal GPT-5.2 leads

GPT-4V: 33.2, GPT-5.2: 51.3 (#7)

Multimodal benchmarks
BenchmarkGPT-4VGPT-5.2
LMArena Vision—1268
Video-MME59.9%—
VPCT—84%
Furniture Assembly—38.3%
LMArena Document—1405

Multilingual Not comparable

GPT-4V: —, GPT-5.2: 53.4 (#67)

Multilingual benchmarks
BenchmarkGPT-4VGPT-5.2
LMArena Non-English—1425
LMArena Chinese—1460
LMArena French—1455
LMArena German—1448
LMArena Japanese—1420
LMArena Korean—1392
LMArena Russian—1440
LMArena Spanish—1433

Instruction Following Not comparable

GPT-4V: —, GPT-5.2: 74.7 (#89)

Instruction Following benchmarks
BenchmarkGPT-4VGPT-5.2
LMArena Instruction Following—1417

Long Context Not comparable

GPT-4V: —, GPT-5.2: 44.0 (#78)

Long Context benchmarks
BenchmarkGPT-4VGPT-5.2
CL-bench—18.2%
LMArena Longer Query—1428

Writing & Preference Not comparable

GPT-4V: —, GPT-5.2: 66.8 (#32)

Writing & Preference benchmarks
BenchmarkGPT-4VGPT-5.2
LMArena Text—1439
LMArena Creative Writing—1401
EQ-Bench Creative Writing—1703
LMArena Multi-Turn—1458

Frequently asked questions

Is GPT-4V better than GPT-5.2?

GPT-5.2 has enough public results to be ranked (#34); GPT-4V does not yet, so treat this comparison as directional.

How many benchmarks do GPT-4V and GPT-5.2 share?

0 benchmarks have published results for both models. GPT-4V has 1 scored results on Noometry and GPT-5.2 has 67.

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