Model comparison
GPT-5.6 Luna vs Qwen1.5-14B
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 32.7 on the Noometry Index.
Last verified . 16 shared benchmarks.
Alibaba (Qwen)Summary
- They share 16 benchmarks with published results for both. GPT-5.6 Luna scores higher in 8 categories and Qwen1.5-14B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 32.4.
- Qwen1.5-14B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.6 Luna | Qwen1.5-14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 54.6 | 32.7 |
| Released | 2026-07-09 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.20 | — |
| Output $ / M tokens | $1.20 | — |
| Results tracked | 52 | 17 |
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Category by category
Coding GPT-5.6 Luna leads
GPT-5.6 Luna: 54.5 (#28), Qwen1.5-14B: 33.1 (#263)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1466 | 1138 |
| DeepSWE | 67.2% | — |
| FrontierCode | 39.8% | — |
| CursorBench | 35.9% | — |
| LMArena WebDev | 1519 | — |
| SciCode | 53.6% | — |
| WeirdML | 60.9% | — |
| ALE-Bench | 1,667 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Luna: 34.4 (#45), Qwen1.5-14B: —
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| APEX-Agents | 43% | — |
| 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), Qwen1.5-14B: 21.4 (#223)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1451 | 1113 |
| ARC-AGI-2 | 59.5% | — |
| SimpleBench | 46.8% | — |
| Kagi LLM Benchmark | 49.1% | — |
| NYT Connections (extended) | 69.4% | — |
| ARC-AGI-1 | 88% | — |
| CritPt | 20.6% | — |
| Chess Puzzles | 40% | — |
| Mystery Game Puzzles | 21% | — |
| DTBench | 89.1% | — |
| LMCA | 48.5% | — |
| Surface Evolver Bench | 61.9% | — |
| Epoch Capabilities Index | 156.39 | — |
Math GPT-5.6 Luna leads
GPT-5.6 Luna: 77.7 (#14), Qwen1.5-14B: 32.4 (#215)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1458 | 1125 |
| FrontierMath (Tiers 1-3) | 82.1% | — |
| FrontierMath Tier 4 | 61% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 60% | — |
Knowledge GPT-5.6 Luna leads
GPT-5.6 Luna: 58.5 (#34), Qwen1.5-14B: 29.8 (#232)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1478 | 1094 |
| GPQA Diamond | 91.6% | — |
| SimpleQA Verified | 41% | — |
| MMLU | — | 68.6% |
Multimodal Not comparable
GPT-5.6 Luna: 42.7 (#28), Qwen1.5-14B: —
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Vision | 1258 | — |
| Blueprint-Bench 2 | 22.6% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1457 | — |
Multilingual GPT-5.6 Luna leads
GPT-5.6 Luna: 52.8 (#78), Qwen1.5-14B: 30.7 (#262)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1417 | 1095 |
| LMArena Chinese | 1470 | 1147 |
| LMArena French | 1456 | 1116 |
| LMArena German | 1454 | 1043 |
| LMArena Japanese | 1411 | 1019 |
| LMArena Russian | 1428 | 1046 |
| LMArena Spanish | 1448 | 1085 |
| LMArena Korean | 1415 | — |
Instruction Following GPT-5.6 Luna leads
GPT-5.6 Luna: 75.6 (#57), Qwen1.5-14B: 56.8 (#271)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1437 | 1102 |
Long Context GPT-5.6 Luna leads
GPT-5.6 Luna: 43.9 (#82), Qwen1.5-14B: 33.7 (#257)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1436 | 1113 |
Writing & Preference GPT-5.6 Luna leads
GPT-5.6 Luna: 68.0 (#29), Qwen1.5-14B: 33.6 (#276)
| Benchmark | GPT-5.6 Luna | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1431 | 1128 |
| LMArena Creative Writing | 1396 | 1091 |
| LMArena Multi-Turn | 1434 | 1110 |
| EQ-Bench Creative Writing | 1829 | — |
| EQ-Bench 4 | 1156 | — |
Frequently asked questions
Is GPT-5.6 Luna better than Qwen1.5-14B?
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 32.7 on the Noometry Index.
Is GPT-5.6 Luna or Qwen1.5-14B better for coding?
GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 33.1 in the Noometry coding category.
How many benchmarks do GPT-5.6 Luna and Qwen1.5-14B share?
16 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and Qwen1.5-14B has 17.