GPT-5.6 Luna vs MiMo-V2.5-Pro
Updated October 21, 2026. 66 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.6 Luna for coding: it scores 61.5 on the Vibe Coding Index against 40.0 for MiMo-V2.5-Pro.
Pick MiMo-V2.5-Pro when output tokens cost 2.0x less, or when a solved task costs $0.03 against $0.04.
- Shared results
- 66
- GPT-5.6 Luna only
- 50
- MiMo-V2.5-Pro only
- 4
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
GPT-5.6 Luna
GPT-5.6 Luna scores 61.5 against 40.0.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 26.0.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 42.1 against 21.3.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Luna
GPT-5.6 Luna leads, 91.7% against 82.6%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.6 Luna
GPT-5.6 Luna leads, 86.0% against 84.6%.
Same board, both measured
Web design
Design Arena: websites
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 1267 against 1256.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5-Pro
GPT-5.6 Luna $0.0008, MiMo-V2.5-Pro $0.0006 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiMo-V2.5-Pro
GPT-5.6 Luna $0.04, MiMo-V2.5-Pro $0.03.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.6 Luna 61.5 from 2 benchmarks, MiMo-V2.5-Pro 40.0 from 1 benchmark.
- Widest category
- Agentic work, 16.0 points apart on average over 5 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5.6 Luna 77.1% against MiMo-V2.5-Pro 34.1%, 43.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Luna $1.20 against MiMo-V2.5-Pro $0.609 per million output tokens, 2.0x apart.
- Context window
- Both take 1.05M tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5.6 Luna | Bars | MiMo-V2.5-Pro | Ties |
|---|---|---|---|---|
| Coding | 11 | 2 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 5 | 0 | ||
| Reasoning | 3 | 3 | ||
| Math | 1 | 2 | ||
| Knowledge | 5 | 4 | ||
| Web design | 2 | 6 | ||
| General | 5 | 16 | ||
| All shared boards | 33 | 33 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index112
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev | 1518 | 1480 | GPT-5.6 Luna |
| AA Coding Index | 71.4 | 60.2 | GPT-5.6 Luna |
| LiveCodeBench (Vals AI) | Not measured | 81.3% | Only MiMo-V2.5-Pro measured |
| SWE-bench Verified (Vals AI) | 93.0% | 74.0% | GPT-5.6 Luna |
| Terminal-Bench 4 (Vals AI) | 11.6% | 0.5% | GPT-5.6 Luna |
| Vibe Code Bench (Vals AI) | 77.1% | 34.1% | GPT-5.6 Luna |
| Code migration (Vals AI) | 44.5% | 21.6% | GPT-5.6 Luna |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only GPT-5.6 Luna measured |
| IOI (Vals AI) | 61.8% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 79.0% | 57.3% | GPT-5.6 Luna |
| Vibe Code Bench 1-100 (Vals AI) | 22.6% | Not measured | Only GPT-5.6 Luna measured |
| SkillsBench (Vals AI) | 60.5% | Not measured | Only GPT-5.6 Luna measured |
| CyberBench (Vals AI) | 73.6% | Not measured | Only GPT-5.6 Luna measured |
| SciCode | 53.6% | 50.6% | GPT-5.6 Luna |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 43.2% | Only MiMo-V2.5-Pro measured |
| FrontierCode | 39.8% | Not measured | Only GPT-5.6 Luna measured |
| WeirdML | 60.9% | Not measured | Only GPT-5.6 Luna measured |
| ALE-Bench | 1667.4 | 899.8 | GPT-5.6 Luna |
| LMArena Text: coding | 1466 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: software and IT | 1463 | 1495 | MiMo-V2.5-Pro |
| LMArena WebDev: React | 1508 | 1469 | GPT-5.6 Luna |
| LMArena WebDev: HTML | 1520 | 1473 | GPT-5.6 Luna |
| LMArena WebDev: from an image | 1517 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 37.3 | 26.0 | GPT-5.6 Luna |
| Epoch Capabilities Index | 156.5 | Not measured | Only GPT-5.6 Luna measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 42.1 | 21.3 | GPT-5.6 Luna |
| LiveBench research | 51.0% | Not measured | Only GPT-5.6 Luna measured |
| LiveBench browser | 68.0% | Not measured | Only GPT-5.6 Luna measured |
| LiveBench long agentic | 30.4% | Not measured | Only GPT-5.6 Luna measured |
| SREBench (Vals AI) | 1.5% | Not measured | Only GPT-5.6 Luna measured |
| Finance Agent (Vals AI) | 55.0% | 41.5% | GPT-5.6 Luna |
| Tax Agent Bench (Vals AI) | 24.8% | 11.5% | GPT-5.6 Luna |
| Legal Research Bench (Vals AI) | 36.5% | 15.9% | GPT-5.6 Luna |
| Excel Modeling Benchmark (Vals AI) | 67.1% | 55.2% | GPT-5.6 Luna |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only GPT-5.6 Luna measured |
| Vals Science Index | 25.3% | Not measured | Only GPT-5.6 Luna measured |
| τ²-Bench Telecom | Not measured | 94.2% | Only MiMo-V2.5-Pro measured |
| APEX-Agents | 43.0% | Not measured | Only GPT-5.6 Luna measured |
| BALROG | 45.6% | Not measured | Only GPT-5.6 Luna measured |
| Vending-Bench 2 | $4,095 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | 82.6% | GPT-5.6 Luna |
| LiveBench reasoning | 85.6% | Not measured | Only GPT-5.6 Luna measured |
| MysteryMechanism (Vals AI) | 14.4% | Not measured | Only GPT-5.6 Luna measured |
| MMMU Pro (Vals AI) | 85.0% | Not measured | Only GPT-5.6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | 91.1% | 86.6% | GPT-5.6 Luna |
| Humanity's Last Exam (Artificial Analysis run) | 39.5% | 35.7% | GPT-5.6 Luna |
| GPQA Diamond (Epoch AI run) | 91.6% | Not measured | Only GPT-5.6 Luna measured |
| ARC-AGI | 88.0% | Not measured | Only GPT-5.6 Luna measured |
| ARC-AGI-2 | 59.5% | Not measured | Only GPT-5.6 Luna measured |
| SimpleBench | 46.8% | Not measured | Only GPT-5.6 Luna measured |
| Chess puzzles | 43.0% | Not measured | Only GPT-5.6 Luna measured |
| Mystery game puzzles | 21.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: hard prompts | 1451 | 1486 | MiMo-V2.5-Pro |
| LMArena Text: expert | 1478 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: hard prompts in English | 1460 | 1494 | MiMo-V2.5-Pro |
| LMArena Vision: diagrams | 1273 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: homework | 1282 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | Not measured | Only GPT-5.6 Luna measured |
| FrontierMath, tiers 1 to 3 | 82.1% | Not measured | Only GPT-5.6 Luna measured |
| FrontierMath, tier 4 | 61.0% | Not measured | Only GPT-5.6 Luna measured |
| ProofBench | 60.0% | 22.0% | GPT-5.6 Luna |
| LMArena Text: math | 1459 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: mathematical work | 1470 | 1491 | MiMo-V2.5-Pro |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index54
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| MMLU Pro | 86.0% | 84.6% | GPT-5.6 Luna |
| LegalBench (Vals AI) | 84.0% | 77.1% | GPT-5.6 Luna |
| CorpFin (Vals AI) | 64.2% | 61.4% | GPT-5.6 Luna |
| TaxEval (Vals AI) | 76.2% | 73.8% | GPT-5.6 Luna |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Luna measured |
| MedCode (Vals AI) | 42.4% | 32.5% | GPT-5.6 Luna |
| SimpleQA Verified | 41.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: science | 1433 | 1482 | MiMo-V2.5-Pro |
| LMArena Text: medicine and healthcare | 1399 | 1473 | MiMo-V2.5-Pro |
| LMArena Text: legal and government | 1446 | 1474 | MiMo-V2.5-Pro |
| LMArena Text: business and finance | 1439 | 1466 | MiMo-V2.5-Pro |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index26
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | 1267 | MiMo-V2.5-Pro |
| Design Arena: UI components | 1250 | 1248 | GPT-5.6 Luna |
| Design Arena: game dev | 1196 | 1261 | MiMo-V2.5-Pro |
| Design Arena: data viz | 1212 | 1257 | MiMo-V2.5-Pro |
| Design Arena: 3D | 1121 | 1244 | MiMo-V2.5-Pro |
| Design Arena: all code categories | 1231 | 1266 | MiMo-V2.5-Pro |
| Design Arena: SVG | 1193 | 1181 | GPT-5.6 Luna |
| Design Arena: ASCII art | 1144 | 1157 | MiMo-V2.5-Pro |
| LiveBench design | 76.0% | Not measured | Only GPT-5.6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index516
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| LiveBench data analysis | 78.0% | Not measured | Only GPT-5.6 Luna measured |
| Public Benefits Bench (Vals AI) | 61.2% | Not measured | Only GPT-5.6 Luna measured |
| SAGE (Vals AI) | 44.2% | Not measured | Only GPT-5.6 Luna measured |
| MedScribe (Vals AI) | 84.4% | 83.7% | GPT-5.6 Luna |
| Vals Multimodal Index | 69.1% | Not measured | Only GPT-5.6 Luna measured |
| IFBench | Not measured | 79.9% | Only MiMo-V2.5-Pro measured |
| Long context reasoning (AA-LCR) | 83.7% | 79.7% | GPT-5.6 Luna |
| DTBench | 89.1% | 84.5% | GPT-5.6 Luna |
| LMCA | 48.5% | 29.5% | GPT-5.6 Luna |
| Surface Evolver Bench | 61.9% | Not measured | Only GPT-5.6 Luna measured |
| Furniture assembly | 42.5% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text | 1431 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: instruction following | 1437 | 1475 | MiMo-V2.5-Pro |
| LMArena Text: creative writing | 1396 | 1438 | MiMo-V2.5-Pro |
| LMArena Vision | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: English | 1441 | 1477 | MiMo-V2.5-Pro |
| LMArena Text: non-English | 1417 | 1448 | MiMo-V2.5-Pro |
| LMArena Text: Chinese | 1470 | 1507 | MiMo-V2.5-Pro |
| LMArena Text: German | 1455 | 1459 | MiMo-V2.5-Pro |
| LMArena Text: Japanese | 1415 | 1410 | GPT-5.6 Luna |
| LMArena Text: Korean | 1415 | 1435 | MiMo-V2.5-Pro |
| LMArena Text: French | 1458 | 1487 | MiMo-V2.5-Pro |
| LMArena Text: Spanish | 1446 | 1469 | MiMo-V2.5-Pro |
| LMArena Text: Russian | 1427 | 1449 | MiMo-V2.5-Pro |
| LMArena Text: Polish | 1405 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: multi-turn | 1434 | 1476 | MiMo-V2.5-Pro |
| LMArena Text: longer queries | 1436 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: writing and language | 1419 | 1451 | MiMo-V2.5-Pro |
| LMArena Text: entertainment and media | 1402 | 1438 | MiMo-V2.5-Pro |
| LMArena Vision: English | 1263 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: Chinese | 1294 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: reading text | 1264 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: humor | 1190 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: creative writing | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Document | 1457 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
MiMo-V2.5-Pro costs less
Repository review
50K input + 3K output tokens
GPT-5.6 Luna costs less
Agent loop
200K input + 10K output tokens
GPT-5.6 Luna costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.6 Luna | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | April 22, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.20 | $0.3045 |
| Output $/Mtok | $1.20 | $0.609 |
| Coding index | 61.5 | 40.0 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.04 | $0.03 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Luna better than MiMo-V2.5-Pro for coding?
Pick GPT-5.6 Luna for coding: it scores 61.5 on the Vibe Coding Index against 40.0 for MiMo-V2.5-Pro. Pick MiMo-V2.5-Pro when output tokens cost 2.0x less, or when a solved task costs $0.03 against $0.04.
Which is cheaper, GPT-5.6 Luna or MiMo-V2.5-Pro?
GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens; MiMo-V2.5-Pro costs $0.3045 and $0.609. Per solved SWE-bench Verified task, GPT-5.6 Luna costs $0.04 and MiMo-V2.5-Pro $0.03.
Which has the bigger context window, GPT-5.6 Luna or MiMo-V2.5-Pro?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-5.6 Luna vs MiMo-V2.5-Pro comparison based on?
66 benchmarks have a result for both models as of October 21, 2026. GPT-5.6 Luna's coding index rests on 2 independent benchmarks and MiMo-V2.5-Pro's on 1. Where only one model has a result, the page says so instead of naming a winner.