Model comparison
GPT-5.6 Luna vs Inkling
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 44.1 on the Noometry Index.
Last verified . 39 shared benchmarks.
Summary
- They share 39 benchmarks with published results for both. GPT-5.6 Luna scores higher in 8 categories and Inkling in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 31.3.
- The biggest single-benchmark swing is ProofBench: 60% for GPT-5.6 Luna and 0% for Inkling.
- GPT-5.6 Luna is cheaper at $0.20 / $1.20 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 66K.
- Inkling has downloadable open weights; the other is API-only.
Side by side
| GPT-5.6 Luna | Inkling | |
|---|---|---|
| Provider | OpenAI | Thinking Machines Lab |
| Noometry Index | 54.6 | 44.1 |
| Released | 2026-07-09 | 2026-07-15 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 66K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.20 | $1.87 |
| Output $ / M tokens | $1.20 | $4.68 |
| Results tracked | 52 | 41 |
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Category by category
Coding GPT-5.6 Luna leads
GPT-5.6 Luna: 54.5 (#28), Inkling: 34.5 (#234)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| FrontierCode | 39.8% | 14% |
| LMArena WebDev | 1519 | 1413 |
| SciCode | 53.6% | 47% |
| WeirdML | 60.9% | 32.3% |
| LMArena Coding | 1466 | 1464 |
| ALE-Bench | 1,667 | 946 |
| DeepSWE | 67.2% | — |
| CursorBench | 35.9% | — |
| FrontierSWE | — | 4.1% |
Agentic & Tool Use GPT-5.6 Luna leads
GPT-5.6 Luna: 34.4 (#45), Inkling: 29.6 (#85)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| APEX-Agents | 43% | 33.8% |
| τ²-bench Banking | — | 25% |
| BALROG | 45.6% | — |
| GDP.pdf | 22.7% | — |
| Vending-Bench 2 | 4,095 | — |
Reasoning GPT-5.6 Luna leads
GPT-5.6 Luna: 47.6 (#43), Inkling: 40.4 (#56)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| ARC-AGI-2 | 59.5% | 36.5% |
| SimpleBench | 46.8% | 50% |
| ARC-AGI-1 | 88% | 79.5% |
| CritPt | 20.6% | 5.4% |
| Chess Puzzles | 40% | 21% |
| LMArena Hard Prompts | 1451 | 1451 |
| DTBench | 89.1% | 87.5% |
| LMCA | 48.5% | 37.6% |
| Epoch Capabilities Index | 156.39 | 148.54 |
| Kagi LLM Benchmark | 49.1% | — |
| NYT Connections (extended) | 69.4% | — |
| Mystery Game Puzzles | 21% | — |
| Surface Evolver Bench | 61.9% | — |
Math GPT-5.6 Luna leads
GPT-5.6 Luna: 77.7 (#14), Inkling: 31.3 (#225)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| FrontierMath (Tiers 1-3) | 82.1% | 33.3% |
| FrontierMath Tier 4 | 61% | 4.9% |
| OTIS Mock AIME 2024-2025 | 98.3% | 88.9% |
| ProofBench | 60% | 0% |
| LMArena Math | 1458 | 1479 |
Knowledge GPT-5.6 Luna leads
GPT-5.6 Luna: 58.5 (#34), Inkling: 55.1 (#49)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| GPQA Diamond | 91.6% | 88.3% |
| SimpleQA Verified | 41% | 40.3% |
| LMArena Expert | 1478 | 1465 |
Multimodal Not comparable
GPT-5.6 Luna: 42.7 (#28), Inkling: —
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| LMArena Vision | 1258 | — |
| Blueprint-Bench 2 | 22.6% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1457 | — |
Multilingual Inkling leads
GPT-5.6 Luna: 52.8 (#78), Inkling: 54.0 (#52)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| LMArena Non-English | 1417 | 1434 |
| LMArena Chinese | 1470 | 1490 |
| LMArena French | 1456 | 1458 |
| LMArena German | 1454 | 1446 |
| LMArena Japanese | 1411 | 1429 |
| LMArena Korean | 1415 | 1404 |
| LMArena Russian | 1428 | 1429 |
| LMArena Spanish | 1448 | 1448 |
Instruction Following Too close to call
GPT-5.6 Luna: 75.6 (#57), Inkling: 75.1 (#71)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| LMArena Instruction Following | 1437 | 1426 |
Long Context Too close to call
GPT-5.6 Luna: 43.9 (#82), Inkling: 43.8 (#86)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| LMArena Longer Query | 1436 | 1434 |
Writing & Preference GPT-5.6 Luna leads
GPT-5.6 Luna: 68.0 (#29), Inkling: 65.2 (#51)
| Benchmark | GPT-5.6 Luna | Inkling |
|---|---|---|
| LMArena Text | 1431 | 1441 |
| LMArena Creative Writing | 1396 | 1387 |
| EQ-Bench Creative Writing | 1829 | 1611 |
| EQ-Bench 4 | 1156 | 1226 |
| LMArena Multi-Turn | 1434 | 1436 |
Frequently asked questions
Is GPT-5.6 Luna better than Inkling?
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 44.1 on the Noometry Index.
Which is cheaper, GPT-5.6 Luna or Inkling?
GPT-5.6 Luna is cheaper. It lists at $0.20 per million input tokens and $1.20 per million output tokens; Inkling lists at $1.87 and $4.68.
Is GPT-5.6 Luna or Inkling better for coding?
GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 34.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Luna does, with 1.05M tokens against 66K.
How many benchmarks do GPT-5.6 Luna and Inkling share?
39 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and Inkling has 41.