Model comparison
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 (54.1 vs 54.7), so choose on price, context window or the category you care about most.
Last verified . 45 shared benchmarks.
GoogleSummary
- They share 45 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 77.5 to 60.5.
- 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.
Side by side
| Gemini 3.5 Flash | GPT-5.6 Luna | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 54.1 | 54.7 |
| Released | 2026-05-19 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $1.50 | $0.20 |
| Output $ / M tokens | $9 | $1.20 |
| Results tracked | 54 | 51 |
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Category by category
Coding GPT-5.6 Luna leads
Gemini 3.5 Flash: 49.1 (#46), GPT-5.6 Luna: 53.9 (#25)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| DeepSWE | 37.4% | 67.2% |
| LMArena WebDev | 1499 | 1517 |
| 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 GPT-5.6 Luna leads
Gemini 3.5 Flash: 24.8 (#107), GPT-5.6 Luna: 35.3 (#37)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| GDP.pdf | 14% | 22.7% |
| Vending-Bench 2 | 5,396 | 4,095 |
| APEX-Agents | 27.5% | — |
| BALROG | — | 45.6% |
| GBAEval | 6.7% | — |
Reasoning Gemini 3.5 Flash leads
Gemini 3.5 Flash: 62.7 (#16), GPT-5.6 Luna: 47.5 (#38)
| 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 | 1452 |
| 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 | 154.55 | 156.32 |
| Kagi LLM Benchmark | — | 49.1% |
| EnigmaEval | 25.4% | — |
| EBR-Bench | 4.8% | — |
| ForecastBench | 59 | — |
Math GPT-5.6 Luna leads
Gemini 3.5 Flash: 60.5 (#30), GPT-5.6 Luna: 77.5 (#12)
| 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 | 1502 | 1455 |
| MathArena Final-Answer Competitions | 76.3% | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge Gemini 3.5 Flash leads
Gemini 3.5 Flash: 66.3 (#10), GPT-5.6 Luna: 58.6 (#31)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| GPQA Diamond | 92.8% | 91.6% |
| SimpleQA Verified | 66.2% | 41% |
| LMArena Expert | 1493 | 1479 |
Multimodal Gemini 3.5 Flash leads
Gemini 3.5 Flash: 45.7 (#13), GPT-5.6 Luna: 43.0 (#22)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Vision | 1311 | 1259 |
| Blueprint-Bench 2 | 33.6% | 22.6% |
| LMArena Document | 1463 | 1457 |
| Furniture Assembly | — | 42.5% |
Multilingual Gemini 3.5 Flash leads
Gemini 3.5 Flash: 57.1 (#12), GPT-5.6 Luna: 53.0 (#73)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Non-English | 1475 | 1418 |
| LMArena Chinese | 1525 | 1469 |
| LMArena French | 1490 | 1457 |
| LMArena German | 1500 | 1459 |
| LMArena Japanese | 1481 | 1416 |
| LMArena Korean | 1453 | 1414 |
| LMArena Russian | 1491 | 1428 |
| LMArena Spanish | 1478 | 1445 |
Instruction Following Gemini 3.5 Flash leads
Gemini 3.5 Flash: 77.2 (#29), GPT-5.6 Luna: 76.0 (#48)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Instruction Following | 1466 | 1440 |
Long Context Gemini 3.5 Flash leads
Gemini 3.5 Flash: 45.3 (#39), GPT-5.6 Luna: 43.9 (#78)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Longer Query | 1481 | 1437 |
Writing & Preference GPT-5.6 Luna leads
Gemini 3.5 Flash: 65.5 (#46), GPT-5.6 Luna: 68.3 (#27)
| Benchmark | Gemini 3.5 Flash | GPT-5.6 Luna |
|---|---|---|
| LMArena Text | 1481 | 1432 |
| LMArena Creative Writing | 1467 | 1397 |
| EQ-Bench 4 | 1087 | 1156 |
| LMArena Multi-Turn | 1482 | 1433 |
| EQ-Bench Creative Writing | — | 1829 |
Frequently asked questions
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 (54.1 vs 54.7), 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: 53.9 versus 49.1 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?
45 benchmarks have published results for both models. Gemini 3.5 Flash has 54 scored results on Noometry and GPT-5.6 Luna has 51.