# Gemini 1.5 Flash (May 2024) vs GPT-5.6 Luna

> GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 33.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-1-5-flash-vs-gpt-5-6-luna
- Last updated: 2026-10-10
- Shared benchmarks: 24

## Summary

- They share 24 benchmarks with published results for both. Gemini 1.5 Flash (May 2024) scores higher in 0 categories and GPT-5.6 Luna in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 22.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 16.3% for Gemini 1.5 Flash (May 2024) and 98.3% for GPT-5.6 Luna.

## Snapshot

| | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 33.2 | 54.6 |
| Rank | 246 | 30 |
| Context | — | 1.05M |
| Input $/M | — | $0.20 |
| Output $/M | — | $1.20 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 1.5 Flash (May 2024): 34.4 (#236)
- GPT-5.6 Luna: 54.5 (#28)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| WeirdML | 24.9% | 60.9% |
| LMArena Coding | 1261 | 1466 |
| DeepSWE | — | 67.2% |
| FrontierCode | — | 39.8% |
| CursorBench | — | 35.9% |
| LMArena WebDev | — | 1519 |
| SciCode | — | 53.6% |
| BigCodeBench Instruct | 43.5% | — |
| BigCodeBench Complete | 55.1% | — |
| ALE-Bench | — | 1,667 |
| HumanEval+ | 75.6% | — |
| MBPP+ | 67.5% | — |

## Agentic & Tool Use

- Gemini 1.5 Flash (May 2024): 26.6 (#102)
- GPT-5.6 Luna: 34.4 (#45)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| BALROG | 14.6% | 45.6% |
| APEX-Agents | — | 43% |
| GDP.pdf | — | 22.7% |
| Vending-Bench 2 | — | 4,095 |

## Reasoning

- Gemini 1.5 Flash (May 2024): 21.7 (#215)
- GPT-5.6 Luna: 47.6 (#43)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| LMArena Hard Prompts | 1257 | 1451 |
| DTBench | 53.8% | 89.1% |
| Epoch Capabilities Index | 129.36 | 156.39 |
| ARC-AGI-2 | — | 59.5% |
| SimpleBench | — | 46.8% |
| Kagi LLM Benchmark | — | 49.1% |
| NYT Connections (extended) | — | 69.4% |
| ARC-AGI-1 | — | 88% |
| CritPt | — | 20.6% |
| Chess Puzzles | — | 40% |
| Mystery Game Puzzles | — | 21% |
| LMCA | — | 48.5% |
| Surface Evolver Bench | — | 61.9% |
| ForecastBench | 53.9 | — |
| PIQA | 87.5% | — |

## Math

- Gemini 1.5 Flash (May 2024): 22.1 (#281)
- GPT-5.6 Luna: 77.7 (#14)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.3% | 98.3% |
| LMArena Math | 1269 | 1458 |
| FrontierMath (Tiers 1-3) | — | 82.1% |
| FrontierMath Tier 4 | — | 61% |
| ProofBench | — | 60% |
| Omni-MATH | 30.4% | — |
| MATH Level 5 | 61.9% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
| GSM8K | 82.4% | — |

## Knowledge

- Gemini 1.5 Flash (May 2024): 26.2 (#260)
- GPT-5.6 Luna: 58.5 (#34)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| GPQA Diamond | 47.3% | 91.6% |
| LMArena Expert | 1233 | 1478 |
| SimpleQA Verified | — | 41% |
| MMLU-Pro | 67.8% | — |
| GPQA (HELM) | 43.7% | — |
| BoolQ | 85.8% | — |
| MMLU | 77.9% | — |

## Multimodal

- Gemini 1.5 Flash (May 2024): 36.0 (#81)
- GPT-5.6 Luna: 42.7 (#28)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| LMArena Vision | 1141 | 1258 |
| Video-MME | 70.3% | — |
| GeoBench | 76% | — |
| Blueprint-Bench 2 | — | 22.6% |
| Furniture Assembly | — | 42.5% |
| LMArena Document | — | 1457 |

## Multilingual

- Gemini 1.5 Flash (May 2024): 42.9 (#189)
- GPT-5.6 Luna: 52.8 (#78)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| LMArena Non-English | 1278 | 1417 |
| LMArena Chinese | 1295 | 1470 |
| LMArena French | 1258 | 1456 |
| LMArena German | 1262 | 1454 |
| LMArena Japanese | 1252 | 1411 |
| LMArena Korean | 1221 | 1415 |
| LMArena Russian | 1288 | 1428 |
| LMArena Spanish | 1243 | 1448 |

## Instruction Following

- Gemini 1.5 Flash (May 2024): 66.8 (#205)
- GPT-5.6 Luna: 75.6 (#57)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| LMArena Instruction Following | 1258 | 1437 |
| IFEval | 83.1% | — |

## Long Context

- Gemini 1.5 Flash (May 2024): 39.0 (#187)
- GPT-5.6 Luna: 43.9 (#82)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| LMArena Longer Query | 1284 | 1436 |

## Writing & Preference

- Gemini 1.5 Flash (May 2024): 48.7 (#196)
- GPT-5.6 Luna: 68.0 (#29)

| Benchmark | Gemini 1.5 Flash (May 2024) | GPT-5.6 Luna |
|---|---|---|
| LMArena Text | 1287 | 1431 |
| LMArena Creative Writing | 1285 | 1396 |
| LMArena Multi-Turn | 1253 | 1434 |
| EQ-Bench Creative Writing | — | 1829 |
| WildBench | 79.2% | — |
| EQ-Bench 4 | — | 1156 |

## FAQ

### Is Gemini 1.5 Flash (May 2024) better than GPT-5.6 Luna?

GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 33.2 on the Noometry Index.

### Is Gemini 1.5 Flash (May 2024) or GPT-5.6 Luna better for coding?

GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 34.4 in the Noometry coding category.

### How many benchmarks do Gemini 1.5 Flash (May 2024) and GPT-5.6 Luna share?

24 benchmarks have published results for both models. Gemini 1.5 Flash (May 2024) has 42 scored results on Noometry and GPT-5.6 Luna has 52.