Model comparison
GPT-5.6 Luna vs Qwen2.5-Max
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 40.7 on the Noometry Index.
Last verified . 18 shared benchmarks.
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. GPT-5.6 Luna scores higher in 8 categories and Qwen2.5-Max 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 36.9.
Side by side
| GPT-5.6 Luna | Qwen2.5-Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 54.6 | 40.7 |
| Released | 2026-07-09 | 2025-01-25 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.20 | — |
| Output $ / M tokens | $1.20 | — |
| Results tracked | 52 | 27 |
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Category by category
Coding GPT-5.6 Luna leads
GPT-5.6 Luna: 54.5 (#28), Qwen2.5-Max: 41.8 (#117)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Coding | 1466 | 1359 |
| DeepSWE | 67.2% | — |
| FrontierCode | 39.8% | — |
| CursorBench | 35.9% | — |
| LMArena WebDev | 1519 | — |
| SciCode | 53.6% | — |
| WeirdML | 60.9% | — |
| LiveBench Coding | — | 64.4% |
| ALE-Bench | 1,667 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Luna: 34.4 (#45), Qwen2.5-Max: —
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| 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), Qwen2.5-Max: 25.6 (#147)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Hard Prompts | 1451 | 1360 |
| Epoch Capabilities Index | 156.39 | 132.53 |
| 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% | — |
| LiveBench Reasoning | — | 51.4% |
| Mystery Game Puzzles | 21% | — |
| DTBench | 89.1% | — |
| LiveBench Data Analysis | — | 67.9% |
| LMCA | 48.5% | — |
| Surface Evolver Bench | 61.9% | — |
| LiveBench | — | 62.3% |
Math GPT-5.6 Luna leads
GPT-5.6 Luna: 77.7 (#14), Qwen2.5-Max: 36.9 (#162)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Math | 1458 | 1369 |
| FrontierMath (Tiers 1-3) | 82.1% | — |
| FrontierMath Tier 4 | 61% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 60% | — |
| LiveBench Math | — | 58.4% |
Knowledge GPT-5.6 Luna leads
GPT-5.6 Luna: 58.5 (#34), Qwen2.5-Max: 35.3 (#186)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Expert | 1478 | 1337 |
| GPQA Diamond | 91.6% | — |
| SimpleQA Verified | 41% | — |
| Confabulations | — | 21.8% |
Multimodal Not comparable
GPT-5.6 Luna: 42.7 (#28), Qwen2.5-Max: —
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| 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), Qwen2.5-Max: 48.1 (#146)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Non-English | 1417 | 1352 |
| LMArena Chinese | 1470 | 1382 |
| LMArena French | 1456 | 1396 |
| LMArena German | 1454 | 1350 |
| LMArena Japanese | 1411 | 1300 |
| LMArena Korean | 1415 | 1304 |
| LMArena Russian | 1428 | 1353 |
| LMArena Spanish | 1448 | 1377 |
Instruction Following GPT-5.6 Luna leads
GPT-5.6 Luna: 75.6 (#57), Qwen2.5-Max: 71.3 (#152)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Instruction Following | 1437 | 1335 |
| LiveBench Instruction Following | — | 75.3% |
Long Context GPT-5.6 Luna leads
GPT-5.6 Luna: 43.9 (#82), Qwen2.5-Max: 41.4 (#142)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Longer Query | 1436 | 1358 |
Writing & Preference GPT-5.6 Luna leads
GPT-5.6 Luna: 68.0 (#29), Qwen2.5-Max: 55.4 (#146)
| Benchmark | GPT-5.6 Luna | Qwen2.5-Max |
|---|---|---|
| LMArena Text | 1431 | 1367 |
| LMArena Creative Writing | 1396 | 1339 |
| LMArena Multi-Turn | 1434 | 1364 |
| Short-Story Creative Writing | — | 72.9% |
| EQ-Bench Creative Writing | 1829 | — |
| EQ-Bench 4 | 1156 | — |
| LiveBench Language | — | 56.3% |
Frequently asked questions
Is GPT-5.6 Luna better than Qwen2.5-Max?
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 40.7 on the Noometry Index.
Is GPT-5.6 Luna or Qwen2.5-Max better for coding?
GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 41.8 in the Noometry coding category.
How many benchmarks do GPT-5.6 Luna and Qwen2.5-Max share?
18 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and Qwen2.5-Max has 27.