Model comparison
GPT-5.1 vs GPT-6 Luna
GPT-6 Luna is the stronger model overall, scoring 53.3 to 49.0 on the Noometry Index.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. GPT-5.1 scores higher in 5 categories and GPT-6 Luna in 5 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Luna leads 76.1 to 52.2.
- The biggest single-benchmark swing is ARC-AGI-2: 17.6% for GPT-5.1 and 59.3% for GPT-6 Luna.
- GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- GPT-6 Luna accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-5.1 | GPT-6 Luna | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 49.0 | 53.3 |
| Released | 2025-11-13 | 2026-09-22 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $1.25 | $0.10 |
| Output $ / M tokens | $10 | $0.50 |
| Results tracked | 63 | 42 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Luna leads
GPT-5.1: 46.4 (#66), GPT-6 Luna: 55.5 (#25)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| LMArena WebDev | 1395 | 1581 |
| SciCode | 43.3% | 54.6% |
| LMArena Coding | 1454 | 1439 |
| ALE-Bench | 1,192 | 1,577 |
| SWE-bench Verified | 68% | — |
| DeepSWE | — | 66.6% |
| FrontierCode | — | 42.4% |
| SWE-bench Verified (bash only) | 66% | — |
| GSO | 13.7% | — |
| WeirdML | 60.8% | — |
| LiveBench Coding | 72.5% | — |
Agentic & Tool Use Too close to call
GPT-5.1: 32.7 (#60), GPT-6 Luna: 33.3 (#54)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| Terminal-Bench | 47.6% | — |
| APEX-Agents | — | 44.3% |
| DeepResearch Bench | 42.8% | — |
| GDP.pdf | — | 23% |
| LMArena Search | 1199 | — |
| Vending-Bench 2 | 1,473 | — |
Reasoning GPT-6 Luna leads
GPT-5.1: 39.8 (#58), GPT-6 Luna: 48.2 (#41)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| ARC-AGI-2 | 17.6% | 59.3% |
| ARC-AGI-1 | 72.8% | 86.7% |
| CritPt | 4.9% | 19.4% |
| Chess Puzzles | 32% | 31% |
| LMArena Hard Prompts | 1457 | 1411 |
| Mystery Game Puzzles | 19% | 7% |
| DTBench | 90.1% | 90.1% |
| LMCA | 43.9% | 44.5% |
| Epoch Capabilities Index | 149.64 | 156.28 |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | — | 68.7% |
| EnigmaEval | 11.2% | — |
| LiveBench Reasoning | 95.8% | — |
| LiveBench Data Analysis | 72.1% | — |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math GPT-6 Luna leads
GPT-5.1: 52.2 (#51), GPT-6 Luna: 76.1 (#15)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.6% | 98.9% |
| LMArena Math | 1447 | 1416 |
| FrontierMath (Tiers 1-3) | — | 78.9% |
| FrontierMath Tier 4 | — | 56.1% |
| ProofBench | — | 64% |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
| FrontierMath (Feb 2025 set) | 31% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GPT-6 Luna leads
GPT-5.1: 50.6 (#71), GPT-6 Luna: 57.0 (#41)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| GPQA Diamond | 87.6% | 90.5% |
| SimpleQA Verified | 48% | 41.4% |
| LMArena Expert | 1470 | 1444 |
| Humanity's Last Exam | 23.7% | — |
| MMLU-Pro | 57.9% | — |
| Vectara Hallucination Rate | 10.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.8 (#19), GPT-6 Luna: 42.4 (#30)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| LMArena Vision | 1250 | 1217 |
| VPCT | 58.7% | — |
| Blueprint-Bench 2 | — | 31.2% |
| Furniture Assembly | — | 44.2% |
| LMArena Document | 1403 | — |
Multilingual GPT-5.1 leads
GPT-5.1: 53.8 (#56), GPT-6 Luna: 50.5 (#117)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| LMArena Non-English | 1431 | 1386 |
| LMArena Chinese | 1495 | 1433 |
| LMArena French | 1450 | 1420 |
| LMArena German | 1438 | 1369 |
| LMArena Japanese | 1453 | 1369 |
| LMArena Korean | 1401 | 1360 |
| LMArena Russian | 1435 | 1394 |
| LMArena Spanish | 1433 | 1393 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), GPT-6 Luna: 74.3 (#99)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| LMArena Instruction Following | 1443 | 1409 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), GPT-6 Luna: 43.0 (#111)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| LMArena Longer Query | 1447 | 1409 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference GPT-5.1 leads
GPT-5.1: 64.5 (#55), GPT-6 Luna: 58.3 (#119)
| Benchmark | GPT-5.1 | GPT-6 Luna |
|---|---|---|
| LMArena Text | 1443 | 1391 |
| LMArena Creative Writing | 1427 | 1363 |
| LMArena Multi-Turn | 1450 | 1396 |
| WildBench | 86.3% | — |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than GPT-6 Luna?
GPT-6 Luna is the stronger model overall, scoring 53.3 to 49.0 on the Noometry Index.
Which is cheaper, GPT-5.1 or GPT-6 Luna?
GPT-6 Luna is cheaper. It lists at $0.10 per million input tokens and $0.50 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or GPT-6 Luna better for coding?
GPT-6 Luna scores higher on coding benchmarks: 55.5 versus 46.4 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5.1 and GPT-6 Luna share?
32 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and GPT-6 Luna has 42.