Model comparison
Gemini 1.5 Pro (May 2024) vs GPT-5.3 Codex
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 32.1 on the Noometry Index.
Last verified . 2 shared benchmarks.
GoogleSummary
- They share 2 benchmarks with published results for both. Gemini 1.5 Pro (May 2024) scores higher in 0 categories and GPT-5.3 Codex in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.3 Codex leads 48.0 to 17.9.
- The biggest single-benchmark swing is WeirdML: 22.2% for Gemini 1.5 Pro (May 2024) and 79.3% for GPT-5.3 Codex.
Side by side
| Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 32.1 | 45.8 |
| Released | 2024-02-15 | 2026-02-05 |
| Weights | Proprietary | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $1.75 |
| Output $ / M tokens | — | $14 |
| Results tracked | 45 | 8 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.3 Codex leads
Gemini 1.5 Pro (May 2024): 34.2 (#241), GPT-5.3 Codex: 48.6 (#56)
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| WeirdML | 22.2% | 79.3% |
| SWE-bench Verified | — | 74.8% |
| LMArena WebDev | — | 1409 |
| BigCodeBench Instruct | 43.8% | — |
| LMArena Coding | 1294 | — |
| BigCodeBench Complete | 57.5% | — |
| CadEval | 34% | — |
| ALE-Bench | — | 1,655 |
| HumanEval+ | 79.3% | — |
| MBPP+ | 74.6% | — |
Agentic & Tool Use GPT-5.3 Codex leads
Gemini 1.5 Pro (May 2024): 17.9 (#145), GPT-5.3 Codex: 48.0 (#9)
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| TheAgentCompany | 3.4% | — |
| Cybench | 7.5% | — |
| BALROG | 21% | — |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |
Reasoning Not comparable
Gemini 1.5 Pro (May 2024): 12.3 (#338), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 131.73 | 156.77 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 27.1% | — |
| LMArena Hard Prompts | 1296 | — |
| DTBench | 59% | — |
| BIG-Bench Hard | 89.2% | — |
| ForecastBench | 58.4 | — |
Math Not comparable
Gemini 1.5 Pro (May 2024): 25.8 (#266), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 23.1% | — |
| Omni-MATH | 36.4% | — |
| LMArena Math | 1315 | — |
| MATH Level 5 | 70.4% | — |
Knowledge Not comparable
Gemini 1.5 Pro (May 2024): 29.4 (#239), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 57.2% | — |
| Humanity's Last Exam | 4.6% | — |
| MMLU-Pro | 73.7% | — |
| Confabulations | 13.5% | — |
| GPQA (HELM) | 53.4% | — |
| LMArena Expert | 1279 | — |
| MMLU | 86.9% | — |
Multimodal Not comparable
Gemini 1.5 Pro (May 2024): 36.8 (#77), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| LMArena Vision | 1161 | — |
| Video-MME | 75% | — |
Multilingual Not comparable
Gemini 1.5 Pro (May 2024): 45.3 (#174), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1312 | — |
| LMArena Chinese | 1331 | — |
| LMArena French | 1302 | — |
| LMArena German | 1286 | — |
| LMArena Japanese | 1292 | — |
| LMArena Korean | 1298 | — |
| LMArena Russian | 1320 | — |
| LMArena Spanish | 1311 | — |
Instruction Following Not comparable
Gemini 1.5 Pro (May 2024): 68.6 (#185), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| IFEval | 83.7% | — |
| LMArena Instruction Following | 1297 | — |
Long Context Not comparable
Gemini 1.5 Pro (May 2024): 39.8 (#169), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1308 | — |
Writing & Preference Not comparable
Gemini 1.5 Pro (May 2024): 52.4 (#172), GPT-5.3 Codex: —
| Benchmark | Gemini 1.5 Pro (May 2024) | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1319 | — |
| LMArena Creative Writing | 1333 | — |
| WildBench | 81.3% | — |
| LMArena Multi-Turn | 1296 | — |
Frequently asked questions
Is Gemini 1.5 Pro (May 2024) better than GPT-5.3 Codex?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 32.1 on the Noometry Index.
Is Gemini 1.5 Pro (May 2024) or GPT-5.3 Codex better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 34.2 in the Noometry coding category.
How many benchmarks do Gemini 1.5 Pro (May 2024) and GPT-5.3 Codex share?
2 benchmarks have published results for both models. Gemini 1.5 Pro (May 2024) has 45 scored results on Noometry and GPT-5.3 Codex has 8.