# Gemini 3.5 Flash vs GPT-5.6 Luna

> Gemini 3.5 Flash and GPT-5.6 Luna score almost the same on the Noometry Index (54.2 vs 54.6), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/gemini-3-5-flash-vs-gpt-5-6-luna
- Last updated: 2026-10-10
- Shared benchmarks: 46

## Summary

- They share 46 benchmarks with published results for both. Gemini 3.5 Flash scores higher in 6 categories and GPT-5.6 Luna in 4 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 60.7.
- The biggest single-benchmark swing is FrontierMath Tier 4: 26.8% for Gemini 3.5 Flash and 61% for GPT-5.6 Luna.
- GPT-5.6 Luna is cheaper at $0.20 / $1.20 per million input/output tokens, against $1.50 / $9 for Gemini 3.5 Flash.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 1.05M.

## Snapshot

| | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 54.2 | 54.6 |
| Rank | 32 | 30 |
| Context | 1.05M | 1.05M |
| Input $/M | $1.50 | $0.20 |
| Output $/M | $9 | $1.20 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.5 Flash: 49.4 (#49)
- GPT-5.6 Luna: 54.5 (#28)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| DeepSWE | 37.4% | 67.2% |
| LMArena WebDev | 1499 | 1519 |
| SciCode | 53.1% | 53.6% |
| WeirdML | 62.6% | 60.9% |
| LMArena Coding | 1492 | 1466 |
| ALE-Bench | 911.02 | 1,667 |
| SWE-bench Verified | 79.3% | — |
| FrontierCode | — | 39.8% |
| CursorBench | — | 35.9% |

## Agentic & Tool Use

- Gemini 3.5 Flash: 24.7 (#114)
- GPT-5.6 Luna: 34.4 (#45)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| APEX-Agents | 27.5% | 43% |
| GDP.pdf | 14% | 22.7% |
| Vending-Bench 2 | 5,396 | 4,095 |
| BALROG | — | 45.6% |
| GBAEval | 6.7% | — |

## Reasoning

- Gemini 3.5 Flash: 62.8 (#18)
- GPT-5.6 Luna: 47.6 (#43)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| ARC-AGI-2 | 72.1% | 59.5% |
| SimpleBench | 76.7% | 46.8% |
| NYT Connections (extended) | 92.6% | 69.4% |
| ARC-AGI-1 | 92.5% | 88% |
| CritPt | 13.1% | 20.6% |
| Chess Puzzles | 50% | 40% |
| LMArena Hard Prompts | 1488 | 1451 |
| Mystery Game Puzzles | 32% | 21% |
| DTBench | 94.7% | 89.1% |
| LMCA | 47.1% | 48.5% |
| Surface Evolver Bench | 58.1% | 61.9% |
| Epoch Capabilities Index | 154.46 | 156.39 |
| Kagi LLM Benchmark | — | 49.1% |
| EnigmaEval | 25.4% | — |
| EBR-Bench | 4.8% | — |
| ForecastBench | 59 | — |

## Math

- Gemini 3.5 Flash: 60.7 (#36)
- GPT-5.6 Luna: 77.7 (#14)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| FrontierMath (Tiers 1-3) | 62.8% | 82.1% |
| FrontierMath Tier 4 | 26.8% | 61% |
| OTIS Mock AIME 2024-2025 | 95.6% | 98.3% |
| ProofBench | 31% | 60% |
| LMArena Math | 1504 | 1458 |
| MathArena Final-Answer Competitions | 76.3% | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |

## Knowledge

- Gemini 3.5 Flash: 66.3 (#11)
- GPT-5.6 Luna: 58.5 (#34)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| GPQA Diamond | 92.8% | 91.6% |
| SimpleQA Verified | 66.2% | 41% |
| LMArena Expert | 1495 | 1478 |

## Multimodal

- Gemini 3.5 Flash: 45.7 (#15)
- GPT-5.6 Luna: 42.7 (#28)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Vision | 1310 | 1258 |
| Blueprint-Bench 2 | 33.6% | 22.6% |
| LMArena Document | 1463 | 1457 |
| Furniture Assembly | — | 42.5% |

## Multilingual

- Gemini 3.5 Flash: 57.0 (#13)
- GPT-5.6 Luna: 52.8 (#78)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Non-English | 1476 | 1417 |
| LMArena Chinese | 1526 | 1470 |
| LMArena French | 1490 | 1456 |
| LMArena German | 1492 | 1454 |
| LMArena Japanese | 1486 | 1411 |
| LMArena Korean | 1451 | 1415 |
| LMArena Russian | 1493 | 1428 |
| LMArena Spanish | 1480 | 1448 |

## Instruction Following

- Gemini 3.5 Flash: 77.0 (#30)
- GPT-5.6 Luna: 75.6 (#57)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Instruction Following | 1467 | 1437 |

## Long Context

- Gemini 3.5 Flash: 45.4 (#38)
- GPT-5.6 Luna: 43.9 (#82)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Longer Query | 1482 | 1436 |

## Writing & Preference

- Gemini 3.5 Flash: 65.5 (#47)
- GPT-5.6 Luna: 68.0 (#29)

| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Text | 1482 | 1431 |
| LMArena Creative Writing | 1470 | 1396 |
| EQ-Bench 4 | 1087 | 1156 |
| LMArena Multi-Turn | 1481 | 1434 |
| EQ-Bench Creative Writing | — | 1829 |

## FAQ

### Is Gemini 3.5 Flash better than GPT-5.6 Luna?

Gemini 3.5 Flash and GPT-5.6 Luna score almost the same on the Noometry Index (54.2 vs 54.6), so choose on price, context window or the category you care about most.

### Which is cheaper, Gemini 3.5 Flash or GPT-5.6 Luna?

GPT-5.6 Luna is cheaper. It lists at $0.20 per million input tokens and $1.20 per million output tokens; Gemini 3.5 Flash lists at $1.50 and $9.

### Is Gemini 3.5 Flash or GPT-5.6 Luna better for coding?

GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 49.4 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.6 Luna does, with 1.05M tokens against 1.05M.

### How many benchmarks do Gemini 3.5 Flash and GPT-5.6 Luna share?

46 benchmarks have published results for both models. Gemini 3.5 Flash has 54 scored results on Noometry and GPT-5.6 Luna has 52.