Model comparison
Gemini 2.5 Pro vs GPT-5.3 Codex
Gemini 2.5 Pro and GPT-5.3 Codex score almost the same on the Noometry Index (45.0 vs 45.8), so choose on price, context window or the category you care about most.
Last verified . 8 shared benchmarks.
GoogleSummary
- They share 8 benchmarks with published results for both. Gemini 2.5 Pro 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 29.2.
- The biggest single-benchmark swing is Terminal-Bench: 32.6% for Gemini 2.5 Pro and 78.4% for GPT-5.3 Codex.
- Gemini 2.5 Pro is cheaper at $1.25 / $10 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 400K.
Side by side
| Gemini 2.5 Pro | GPT-5.3 Codex | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 45.0 | 45.8 |
| Released | 2025-03-25 | 2026-02-05 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 66K | 128K |
| Input $ / M tokens | $1.25 | $1.75 |
| Output $ / M tokens | $10 | $14 |
| Results tracked | 78 | 8 |
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Category by category
Coding GPT-5.3 Codex leads
Gemini 2.5 Pro: 42.4 (#101), GPT-5.3 Codex: 48.6 (#56)
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| SWE-bench Verified | 57.6% | 74.8% |
| LMArena WebDev | 1227 | 1409 |
| WeirdML | 54% | 79.3% |
| ALE-Bench | 785.52 | 1,655 |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| SciCode | 42.8% | — |
| GSO | 3.9% | — |
| LiveBench Coding | 85.9% | — |
| LMArena Coding | 1452 | — |
| CadEval | 64% | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use GPT-5.3 Codex leads
Gemini 2.5 Pro: 29.2 (#88), GPT-5.3 Codex: 48.0 (#9)
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | 32.6% | 78.4% |
| METR Time Horizons | 55.4% | 74.5% |
| Vending-Bench 2 | 573.64 | 5,940 |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
Reasoning Not comparable
Gemini 2.5 Pro: 28.8 (#99), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 145.32 | 156.77 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| ARC-AGI-1 | 41% | — |
| CritPt | 2% | — |
| Chess Puzzles | 20% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| LMArena Hard Prompts | 1455 | — |
| DTBench | 82.4% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| ForecastBench | 61.3 | — |
| LiveBench | 82.3% | — |
Math Not comparable
Gemini 2.5 Pro: 32.5 (#213), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| OTIS Mock AIME 2024-2025 | 84.7% | — |
| Omni-MATH | 41.6% | — |
| LiveBench Math | 90.2% | — |
| LMArena Math | 1450 | — |
| MATH Level 5 | 95.9% | — |
| FrontierMath (Feb 2025 set) | 14.1% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Not comparable
Gemini 2.5 Pro: 56.0 (#46), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 85.3% | — |
| Humanity's Last Exam | 21.6% | — |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| GPQA (HELM) | 74.9% | — |
| LMArena Expert | 1452 | — |
Multimodal Not comparable
Gemini 2.5 Pro: 45.2 (#18), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| LMArena Vision | 1263 | — |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |
Multilingual Not comparable
Gemini 2.5 Pro: 55.3 (#31), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1451 | — |
| LMArena Chinese | 1507 | — |
| LMArena French | 1472 | — |
| LMArena German | 1487 | — |
| LMArena Japanese | 1461 | — |
| LMArena Korean | 1434 | — |
| LMArena Russian | 1461 | — |
| LMArena Spanish | 1473 | — |
Instruction Following Not comparable
Gemini 2.5 Pro: 75.0 (#75), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
| LMArena Instruction Following | 1437 | — |
Long Context Not comparable
Gemini 2.5 Pro: 59.8 (#5), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| Fiction.LiveBench | 91.7% | — |
| LMArena Longer Query | 1449 | — |
Writing & Preference Not comparable
Gemini 2.5 Pro: 63.7 (#62), GPT-5.3 Codex: —
| Benchmark | Gemini 2.5 Pro | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1458 | — |
| LMArena Creative Writing | 1454 | — |
| Short-Story Creative Writing | 83.8% | — |
| EQ-Bench Creative Writing | 1421 | — |
| WildBench | 85.7% | — |
| LMArena Multi-Turn | 1453 | — |
| LiveBench Language | 67.8% | — |
Frequently asked questions
Is Gemini 2.5 Pro better than GPT-5.3 Codex?
Gemini 2.5 Pro and GPT-5.3 Codex score almost the same on the Noometry Index (45.0 vs 45.8), so choose on price, context window or the category you care about most.
Which is cheaper, Gemini 2.5 Pro or GPT-5.3 Codex?
Gemini 2.5 Pro is cheaper. It lists at $1.25 per million input tokens and $10 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is Gemini 2.5 Pro or GPT-5.3 Codex better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 42.4 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Pro does, with 1.05M tokens against 400K.
How many benchmarks do Gemini 2.5 Pro and GPT-5.3 Codex share?
8 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and GPT-5.3 Codex has 8.