Model comparison

Gemini 1.5 Pro (May 2024) vs GPT-5-Codex

GPT-5-Codex is the stronger model overall, scoring 37.9 to 32.1 on the Noometry Index.

Last verified . 1 shared benchmarks.

Gemini 1.5 Pro (May 2024) Google

32.1

Rank #261 Confirmed

GPT-5-Codex OpenAI

37.9

Rank #192 Reported

Summary

  • They share 1 benchmark with published results for both. Gemini 1.5 Pro (May 2024) scores higher in 0 categories and GPT-5-Codex in 3 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GPT-5-Codex leads 30.9 to 12.3.
  • The biggest single-benchmark swing is WeirdML: 22.2% for Gemini 1.5 Pro (May 2024) and 54.5% for GPT-5-Codex.

Side by side

Gemini 1.5 Pro (May 2024) and GPT-5-Codex specifications
Gemini 1.5 Pro (May 2024)GPT-5-Codex
ProviderGoogleOpenAI
Noometry Index32.137.9
Released2024-02-152025-09-15
WeightsProprietaryProprietary
Context window—400K
Max output—128K
Input $ / M tokens—$1.25
Output $ / M tokens—$10
Results tracked453

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Category by category

Coding GPT-5-Codex leads

Gemini 1.5 Pro (May 2024): 34.2 (#241), GPT-5-Codex: 42.4 (#103)

Coding benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
WeirdML22.2%54.5%
BigCodeBench Instruct43.8%—
LMArena Coding1294—
BigCodeBench Complete57.5%—
CadEval34%—
HumanEval+79.3%—
MBPP+74.6%—

Agentic & Tool Use GPT-5-Codex leads

Gemini 1.5 Pro (May 2024): 17.9 (#145), GPT-5-Codex: 31.0 (#72)

Agentic & Tool Use benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
Terminal-Bench—44.3%
TheAgentCompany3.4%—
Cybench7.5%—
BALROG21%—

Reasoning GPT-5-Codex leads

Gemini 1.5 Pro (May 2024): 12.3 (#338), GPT-5-Codex: 30.9 (#83)

Reasoning benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
ARC-AGI-20.8%—
SimpleBench27.1%—
Kagi LLM Benchmark—70.3%
LMArena Hard Prompts1296—
DTBench59%—
BIG-Bench Hard89.2%—
Epoch Capabilities Index131.73—
ForecastBench58.4—

Math Not comparable

Gemini 1.5 Pro (May 2024): 25.8 (#266), GPT-5-Codex: —

Math benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
OTIS Mock AIME 2024-202523.1%—
Omni-MATH36.4%—
LMArena Math1315—
MATH Level 570.4%—

Knowledge Not comparable

Gemini 1.5 Pro (May 2024): 29.4 (#239), GPT-5-Codex: —

Knowledge benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
GPQA Diamond57.2%—
Humanity's Last Exam4.6%—
MMLU-Pro73.7%—
Confabulations13.5%—
GPQA (HELM)53.4%—
LMArena Expert1279—
MMLU86.9%—

Multimodal Not comparable

Gemini 1.5 Pro (May 2024): 36.8 (#77), GPT-5-Codex: —

Multimodal benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
LMArena Vision1161—
Video-MME75%—

Multilingual Not comparable

Gemini 1.5 Pro (May 2024): 45.3 (#174), GPT-5-Codex: —

Multilingual benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
LMArena Non-English1312—
LMArena Chinese1331—
LMArena French1302—
LMArena German1286—
LMArena Japanese1292—
LMArena Korean1298—
LMArena Russian1320—
LMArena Spanish1311—

Instruction Following Not comparable

Gemini 1.5 Pro (May 2024): 68.6 (#185), GPT-5-Codex: —

Instruction Following benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
IFEval83.7%—
LMArena Instruction Following1297—

Long Context Not comparable

Gemini 1.5 Pro (May 2024): 39.8 (#169), GPT-5-Codex: —

Long Context benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
LMArena Longer Query1308—

Writing & Preference Not comparable

Gemini 1.5 Pro (May 2024): 52.4 (#172), GPT-5-Codex: —

Writing & Preference benchmarks
BenchmarkGemini 1.5 Pro (May 2024)GPT-5-Codex
LMArena Text1319—
LMArena Creative Writing1333—
WildBench81.3%—
LMArena Multi-Turn1296—

Frequently asked questions

Is Gemini 1.5 Pro (May 2024) better than GPT-5-Codex?

GPT-5-Codex is the stronger model overall, scoring 37.9 to 32.1 on the Noometry Index.

Is Gemini 1.5 Pro (May 2024) or GPT-5-Codex better for coding?

GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 34.2 in the Noometry coding category.

How many benchmarks do Gemini 1.5 Pro (May 2024) and GPT-5-Codex share?

1 benchmark has published results for both models. Gemini 1.5 Pro (May 2024) has 45 scored results on Noometry and GPT-5-Codex has 3.

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