Model comparison
Gemini 2.5 Pro vs GPT-5.2 Pro
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 45.0 on the Noometry Index. Gemini 2.5 Pro costs 17× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
GoogleSummary
- They share 7 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 0 categories and GPT-5.2 Pro in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.2 Pro leads 65.3 to 32.5.
- The biggest single-benchmark swing is ARC-AGI-1: 41% for Gemini 2.5 Pro and 90.5% for GPT-5.2 Pro.
- Gemini 2.5 Pro is cheaper at $1.25 / $10 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 400K.
Side by side
| Gemini 2.5 Pro | GPT-5.2 Pro | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 45.0 | 52.3 |
| Released | 2025-03-25 | 2025-12-11 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 66K | 128K |
| Input $ / M tokens | $1.25 | $21 |
| Output $ / M tokens | $10 | $168 |
| Results tracked | 78 | 8 |
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Category by category
Coding Not comparable
Gemini 2.5 Pro: 42.4 (#101), GPT-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| SWE-bench Verified | 57.6% | — |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| LMArena WebDev | 1227 | — |
| SciCode | 42.8% | — |
| GSO | 3.9% | — |
| WeirdML | 54% | — |
| LiveBench Coding | 85.9% | — |
| LMArena Coding | 1452 | — |
| CadEval | 64% | — |
| ALE-Bench | 785.52 | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Pro: 29.2 (#88), GPT-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| Terminal-Bench | 32.6% | — |
| 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 | — |
| METR Time Horizons | 55.4% | — |
| Vending-Bench 2 | 573.64 | — |
Reasoning GPT-5.2 Pro leads
Gemini 2.5 Pro: 28.8 (#99), GPT-5.2 Pro: 51.5 (#33)
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| ARC-AGI-2 | 4.9% | 54.2% |
| SimpleBench | 62.4% | 57.4% |
| ARC-AGI-1 | 41% | 90.5% |
| Epoch Capabilities Index | 145.32 | 155.4 |
| Kagi LLM Benchmark | 70.3% | — |
| NYT Connections (extended) | — | 79.3% |
| 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 GPT-5.2 Pro leads
Gemini 2.5 Pro: 32.5 (#213), GPT-5.2 Pro: 65.3 (#29)
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 24.6% | 74% |
| FrontierMath Tier 4 | 0% | 46% |
| FrontierMath Tier 4 (v1) | 4.2% | 31.3% |
| 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% | — |
Knowledge Not comparable
Gemini 2.5 Pro: 56.0 (#46), GPT-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| 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-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| 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-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| 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-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
| LMArena Instruction Following | 1437 | — |
Long Context Not comparable
Gemini 2.5 Pro: 59.8 (#5), GPT-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| Fiction.LiveBench | 91.7% | — |
| LMArena Longer Query | 1449 | — |
Writing & Preference Not comparable
Gemini 2.5 Pro: 63.7 (#62), GPT-5.2 Pro: —
| Benchmark | Gemini 2.5 Pro | GPT-5.2 Pro |
|---|---|---|
| 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-5.2 Pro?
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 45.0 on the Noometry Index. Gemini 2.5 Pro costs 17× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Pro or GPT-5.2 Pro?
Gemini 2.5 Pro is cheaper. It lists at $1.25 per million input tokens and $10 per million output tokens; GPT-5.2 Pro lists at $21 and $168.
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-5.2 Pro share?
7 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and GPT-5.2 Pro has 8.