Model comparison
GPT-5.6 Luna vs MiMo-V2.5-Pro
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 45.2 on the Noometry Index.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. GPT-5.6 Luna scores higher in 5 categories and MiMo-V2.5-Pro in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 40.0.
- The biggest single-benchmark swing is ProofBench: 60% for GPT-5.6 Luna and 22% for MiMo-V2.5-Pro.
- GPT-5.6 Luna is cheaper at $0.20 / $1.20 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.5-Pro.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 1.05M.
- MiMo-V2.5-Pro has downloadable open weights; the other is API-only.
Side by side
| GPT-5.6 Luna | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 54.6 | 45.2 |
| Released | 2026-07-09 | 2026-04-22 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.20 | $0.43 |
| Output $ / M tokens | $1.20 | $0.87 |
| Results tracked | 52 | 27 |
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Category by category
Coding GPT-5.6 Luna leads
GPT-5.6 Luna: 54.5 (#28), MiMo-V2.5-Pro: 47.4 (#60)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| LMArena WebDev | 1519 | 1479 |
| SciCode | 53.6% | 50.2% |
| LMArena Coding | 1466 | 1503 |
| ALE-Bench | 1,667 | 899.8 |
| DeepSWE | 67.2% | — |
| FrontierCode | 39.8% | — |
| CursorBench | 35.9% | — |
| WeirdML | 60.9% | — |
Agentic & Tool Use Not comparable
GPT-5.6 Luna: 34.4 (#45), MiMo-V2.5-Pro: —
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| 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), MiMo-V2.5-Pro: 26.8 (#130)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| NYT Connections (extended) | 69.4% | 34.4% |
| CritPt | 20.6% | 4% |
| LMArena Hard Prompts | 1451 | 1488 |
| DTBench | 89.1% | 84.5% |
| LMCA | 48.5% | 29.5% |
| ARC-AGI-2 | 59.5% | — |
| SimpleBench | 46.8% | — |
| Kagi LLM Benchmark | 49.1% | — |
| ARC-AGI-1 | 88% | — |
| Chess Puzzles | 40% | — |
| Mystery Game Puzzles | 21% | — |
| Surface Evolver Bench | 61.9% | — |
| Epoch Capabilities Index | 156.39 | — |
Math GPT-5.6 Luna leads
GPT-5.6 Luna: 77.7 (#14), MiMo-V2.5-Pro: 40.0 (#96)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| ProofBench | 60% | 22% |
| LMArena Math | 1458 | 1481 |
| FrontierMath (Tiers 1-3) | 82.1% | — |
| FrontierMath Tier 4 | 61% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
Knowledge GPT-5.6 Luna leads
GPT-5.6 Luna: 58.5 (#34), MiMo-V2.5-Pro: 42.2 (#98)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1478 | 1503 |
| GPQA Diamond | 91.6% | — |
| SimpleQA Verified | 41% | — |
Multimodal Not comparable
GPT-5.6 Luna: 42.7 (#28), MiMo-V2.5-Pro: —
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Vision | 1258 | — |
| Blueprint-Bench 2 | 22.6% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1457 | — |
Multilingual MiMo-V2.5-Pro leads
GPT-5.6 Luna: 52.8 (#78), MiMo-V2.5-Pro: 55.1 (#34)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1417 | 1449 |
| LMArena Chinese | 1470 | 1507 |
| LMArena French | 1456 | 1488 |
| LMArena German | 1454 | 1458 |
| LMArena Japanese | 1411 | 1412 |
| LMArena Korean | 1415 | 1437 |
| LMArena Russian | 1428 | 1450 |
| LMArena Spanish | 1448 | 1471 |
Instruction Following MiMo-V2.5-Pro leads
GPT-5.6 Luna: 75.6 (#57), MiMo-V2.5-Pro: 77.5 (#21)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1437 | 1477 |
Long Context MiMo-V2.5-Pro leads
GPT-5.6 Luna: 43.9 (#82), MiMo-V2.5-Pro: 45.4 (#37)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1436 | 1483 |
Writing & Preference GPT-5.6 Luna leads
GPT-5.6 Luna: 68.0 (#29), MiMo-V2.5-Pro: 65.3 (#49)
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1431 | 1465 |
| LMArena Creative Writing | 1396 | 1440 |
| EQ-Bench Creative Writing | 1829 | 1493 |
| EQ-Bench 4 | 1156 | 1208 |
| LMArena Multi-Turn | 1434 | 1477 |
Frequently asked questions
Is GPT-5.6 Luna better than MiMo-V2.5-Pro?
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 45.2 on the Noometry Index.
Which is cheaper, GPT-5.6 Luna or MiMo-V2.5-Pro?
GPT-5.6 Luna is cheaper. It lists at $0.20 per million input tokens and $1.20 per million output tokens; MiMo-V2.5-Pro lists at $0.43 and $0.87.
Is GPT-5.6 Luna or MiMo-V2.5-Pro better for coding?
GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 47.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Luna does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-5.6 Luna and MiMo-V2.5-Pro share?
27 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and MiMo-V2.5-Pro has 27.