Model comparison
Gemini 3.6 Flash vs GPT-5.2 Pro
Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 52.3 on the Noometry Index.
Last verified . 6 shared benchmarks.
Summary
- They share 6 benchmarks with published results for both. Gemini 3.6 Flash scores higher in 1 category and GPT-5.2 Pro in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.2 Pro leads 65.3 to 57.3.
- The biggest single-benchmark swing is FrontierMath Tier 4: 22% for Gemini 3.6 Flash and 46% for GPT-5.2 Pro.
- Gemini 3.6 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- Gemini 3.6 Flash accepts more context: 1.05M tokens versus 400K.
Side by side
| Gemini 3.6 Flash | GPT-5.2 Pro | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 54.1 | 52.3 |
| Released | 2026-07-21 | 2025-12-11 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.75 | $21 |
| Output $ / M tokens | $3.75 | $168 |
| Results tracked | 46 | 8 |
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Category by category
Coding Not comparable
Gemini 3.6 Flash: 50.0 (#48), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| DeepSWE | 46.7% | — |
| FrontierCode | 34.4% | — |
| LMArena WebDev | 1538 | — |
| SciCode | 52.7% | — |
| WeirdML | 56.1% | — |
| LMArena Coding | 1491 | — |
| ALE-Bench | 715.52 | — |
Agentic & Tool Use Not comparable
Gemini 3.6 Flash: 32.3 (#65), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| APEX-Agents | 46.9% | — |
| GDP.pdf | 14% | — |
Reasoning Gemini 3.6 Flash leads
Gemini 3.6 Flash: 58.8 (#22), GPT-5.2 Pro: 51.5 (#33)
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| ARC-AGI-2 | 60.4% | 54.2% |
| NYT Connections (extended) | 89% | 79.3% |
| ARC-AGI-1 | 91.2% | 90.5% |
| Epoch Capabilities Index | 154.25 | 155.4 |
| SimpleBench | — | 57.4% |
| CritPt | 10.6% | — |
| Chess Puzzles | 43% | — |
| LMArena Hard Prompts | 1485 | — |
| Mystery Game Puzzles | 30% | — |
| DTBench | 95.5% | — |
| LMCA | 44.9% | — |
Math GPT-5.2 Pro leads
Gemini 3.6 Flash: 57.3 (#40), GPT-5.2 Pro: 65.3 (#29)
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 58.9% | 74% |
| FrontierMath Tier 4 | 22% | 46% |
| MathArena Final-Answer Competitions | 70.8% | — |
| OTIS Mock AIME 2024-2025 | 94.2% | — |
| ProofBench | 36% | — |
| LMArena Math | 1505 | — |
| FrontierMath Tier 4 (v1) | — | 31.3% |
Knowledge Not comparable
Gemini 3.6 Flash: 67.8 (#8), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| GPQA Diamond | 94.1% | — |
| SimpleQA Verified | 66.2% | — |
| LMArena Expert | 1488 | — |
Multimodal Not comparable
Gemini 3.6 Flash: 38.5 (#64), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| LMArena Vision | 1298 | — |
| Blueprint-Bench 2 | 31.2% | — |
| Furniture Assembly | 23.3% | — |
| LMArena Document | 1456 | — |
Multilingual Not comparable
Gemini 3.6 Flash: 56.5 (#19), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| LMArena Non-English | 1469 | — |
| LMArena Chinese | 1531 | — |
| LMArena French | 1504 | — |
| LMArena German | 1478 | — |
| LMArena Japanese | 1476 | — |
| LMArena Korean | 1431 | — |
| LMArena Russian | 1487 | — |
| LMArena Spanish | 1475 | — |
Instruction Following Not comparable
Gemini 3.6 Flash: 77.0 (#33), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| LMArena Instruction Following | 1466 | — |
Long Context Not comparable
Gemini 3.6 Flash: 45.1 (#50), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| LMArena Longer Query | 1474 | — |
Writing & Preference Not comparable
Gemini 3.6 Flash: 68.2 (#27), GPT-5.2 Pro: —
| Benchmark | Gemini 3.6 Flash | GPT-5.2 Pro |
|---|---|---|
| LMArena Text | 1479 | — |
| LMArena Creative Writing | 1465 | — |
| EQ-Bench Creative Writing | 1604 | — |
| LMArena Multi-Turn | 1481 | — |
Frequently asked questions
Is Gemini 3.6 Flash better than GPT-5.2 Pro?
Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 52.3 on the Noometry Index.
Which is cheaper, Gemini 3.6 Flash or GPT-5.2 Pro?
Gemini 3.6 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.2 Pro lists at $21 and $168.
Which has the bigger context window?
Gemini 3.6 Flash does, with 1.05M tokens against 400K.
How many benchmarks do Gemini 3.6 Flash and GPT-5.2 Pro share?
6 benchmarks have published results for both models. Gemini 3.6 Flash has 46 scored results on Noometry and GPT-5.2 Pro has 8.