Model comparison
Gemini 2.5 Flash-Lite vs GPT-6 Luna
GPT-6 Luna is the stronger model overall, scoring 53.3 to 37.0 on the Noometry Index.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GPT-6 Luna in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Luna leads 76.1 to 38.0.
- The biggest single-benchmark swing is DTBench: 62.8% for Gemini 2.5 Flash-Lite and 90.1% for GPT-6 Luna.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
- GPT-6 Luna accepts more context: 1.05M tokens versus 1.05M.
Side by side
| Gemini 2.5 Flash-Lite | GPT-6 Luna | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 37.0 | 53.3 |
| Released | 2025-06-17 | 2026-09-22 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.10 | $0.10 |
| Output $ / M tokens | $0.40 | $0.50 |
| Results tracked | 33 | 42 |
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Category by category
Coding GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 38.5 (#173), GPT-6 Luna: 55.5 (#25)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Coding | 1373 | 1439 |
| ALE-Bench | 325.9 | 1,577 |
| DeepSWE | — | 66.6% |
| FrontierCode | — | 42.4% |
| LMArena WebDev | — | 1581 |
| SciCode | — | 54.6% |
| WeirdML | 35.2% | — |
Agentic & Tool Use GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 28.0 (#96), GPT-6 Luna: 33.3 (#54)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| APEX-Agents | — | 44.3% |
| Berkeley Function Calling Leaderboard | 36.9% | — |
| GDP.pdf | — | 23% |
Reasoning GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 22.2 (#205), GPT-6 Luna: 48.2 (#41)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1411 |
| DTBench | 62.8% | 90.1% |
| LMCA | 18.1% | 44.5% |
| Epoch Capabilities Index | 133.94 | 156.28 |
| ARC-AGI-2 | — | 59.3% |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 68.7% |
| ARC-AGI-1 | — | 86.7% |
| CritPt | — | 19.4% |
| Chess Puzzles | — | 31% |
| Mystery Game Puzzles | — | 7% |
Math GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 38.0 (#144), GPT-6 Luna: 76.1 (#15)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Math | 1373 | 1416 |
| FrontierMath (Tiers 1-3) | — | 78.9% |
| FrontierMath Tier 4 | — | 56.1% |
| OTIS Mock AIME 2024-2025 | — | 98.9% |
| ProofBench | — | 64% |
| Omni-MATH | 48% | — |
Knowledge GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 32.5 (#210), GPT-6 Luna: 57.0 (#41)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Expert | 1373 | 1444 |
| GPQA Diamond | — | 90.5% |
| SimpleQA Verified | — | 41.4% |
| MMLU-Pro | 53.7% | — |
| Vectara Hallucination Rate | 3.3% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 29.1 (#114), GPT-6 Luna: 42.4 (#30)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Vision | 1198 | 1217 |
| VPCT | 30% | — |
| Blueprint-Bench 2 | — | 31.2% |
| Furniture Assembly | — | 44.2% |
Multilingual GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 49.3 (#134), GPT-6 Luna: 50.5 (#117)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Non-English | 1369 | 1386 |
| LMArena Chinese | 1404 | 1433 |
| LMArena French | 1388 | 1420 |
| LMArena German | 1389 | 1369 |
| LMArena Japanese | 1359 | 1369 |
| LMArena Korean | 1360 | 1360 |
| LMArena Russian | 1373 | 1394 |
| LMArena Spanish | 1396 | 1393 |
Instruction Following GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 70.0 (#168), GPT-6 Luna: 74.3 (#99)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Instruction Following | 1367 | 1409 |
| IFEval | 81% | — |
Long Context GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 33.3 (#262), GPT-6 Luna: 43.0 (#111)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Longer Query | 1373 | 1409 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference GPT-6 Luna leads
Gemini 2.5 Flash-Lite: 56.8 (#135), GPT-6 Luna: 58.3 (#119)
| Benchmark | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|
| LMArena Text | 1379 | 1391 |
| LMArena Creative Writing | 1367 | 1363 |
| LMArena Multi-Turn | 1366 | 1396 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GPT-6 Luna?
GPT-6 Luna is the stronger model overall, scoring 53.3 to 37.0 on the Noometry Index.
Which is cheaper, Gemini 2.5 Flash-Lite or GPT-6 Luna?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-6 Luna lists at $0.10 and $0.50.
Is Gemini 2.5 Flash-Lite or GPT-6 Luna better for coding?
GPT-6 Luna scores higher on coding benchmarks: 55.5 versus 38.5 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 1.05M.
How many benchmarks do Gemini 2.5 Flash-Lite and GPT-6 Luna share?
22 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GPT-6 Luna has 42.