GPT-6 Luna vs MiMo-V2.5-Pro
GPT-6 Luna leads MiMo-V2.5-Pro on coding, 57.3 to 31.6 on the Vibe Coding Index, and GPT-6 Luna costs 1.8x less per output token ($0.50 vs $0.9152 per million). Updated October 22, 2026; 57 benchmarks have a result for both.
GPT-6 Luna or MiMo-V2.5-Pro: which to pick
Pick GPT-6 Luna for coding: it scores 57.3 on the Vibe Coding Index against 31.6 for MiMo-V2.5-Pro.
Pick MiMo-V2.5-Pro for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 57
- GPT-6 Luna only
- 46
- MiMo-V2.5-Pro only
- 13
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
GPT-6 Luna
GPT-6 Luna scores 57.3 against 31.6.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6 Luna
GPT-6 Luna leads, 38.1 against 26.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiMo-V2.5-Pro has a AA Agentic Index result, 21.3.
Directional only
Reasoning
GPQA Diamond
No call
Only MiMo-V2.5-Pro has a GPQA Diamond result, 82.6%.
Directional only
Knowledge
MMLU Pro
No call
Only MiMo-V2.5-Pro has a MMLU Pro result, 84.6%.
Directional only
Web design
Design Arena: websites
GPT-6 Luna
GPT-6 Luna leads, 1271 against 1266.
Same board, both measured
General
Vals Index
No call
Only GPT-6 Luna has a Vals Index result, 52.3%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Luna
GPT-6 Luna $0.0003, MiMo-V2.5-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiMo-V2.5-Pro has the number, $0.03.
Directional only
At a glance
- Coding index
- GPT-6 Luna 57.3 from 5 benchmarks, MiMo-V2.5-Pro 31.6 from 4 benchmarks.
- Widest category
- Math, 21.6 points apart on average over 3 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-6 Luna 81.7% against MiMo-V2.5-Pro 34.1%, 47.5 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Luna $0.50 against MiMo-V2.5-Pro $0.9152 per million output tokens, 1.8x 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-6 Luna | Bars | MiMo-V2.5-Pro | Ties |
|---|---|---|---|---|
| Coding | 9 | 2 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 1 | 3 | ||
| Math | 1 | 2 | ||
| Knowledge | 1 | 4 | ||
| Web design | 4 | 4 | ||
| General | 3 | 18 | ||
| All shared boards | 24 | 33 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index92
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev | 1578 | 1480 | GPT-6 Luna |
| AA Coding Index | Not measured | 60.2 | Only MiMo-V2.5-Pro measured |
| LiveCodeBench (Vals AI) | Not measured | 81.3% | Only MiMo-V2.5-Pro measured |
| SWE-bench Verified (Vals AI) | Not measured | 74.0% | Only MiMo-V2.5-Pro measured |
| Terminal-Bench 4 (Vals AI) | 13.6% | 0.5% | GPT-6 Luna |
| Vibe Code Bench (Vals AI) | 81.7% | 34.1% | GPT-6 Luna |
| Code migration (Vals AI) | 42.5% | 21.6% | GPT-6 Luna |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-6 Luna measured |
| IOI (Vals AI) | 55.6% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 73.0% | 57.3% | GPT-6 Luna |
| SWE-bench Multimodal (Vals AI) | 37.5% | Not measured | Only GPT-6 Luna measured |
| CyberBench (Vals AI) | 76.3% | Not measured | Only GPT-6 Luna measured |
| SciCode | 54.6% | 50.6% | GPT-6 Luna |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 43.2% | Only MiMo-V2.5-Pro measured |
| FrontierCode | 42.4% | Not measured | Only GPT-6 Luna measured |
| ALE-Bench | 1576.9 | 899.8 | GPT-6 Luna |
| LMArena Text: coding | 1437 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: software and IT | 1423 | 1495 | MiMo-V2.5-Pro |
| LMArena WebDev: React | 1573 | 1469 | GPT-6 Luna |
| LMArena WebDev: HTML | 1595 | 1473 | GPT-6 Luna |
| LMArena WebDev: from an image | 1571 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.1 | 26.0 | GPT-6 Luna |
| Epoch Capabilities Index | 156.8 | Not measured | Only GPT-6 Luna measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.3 | Only MiMo-V2.5-Pro measured |
| Design Arena: agents building web apps | 1191 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building full-stack apps | 1158 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building mobile apps | 1134 | Not measured | Only GPT-6 Luna measured |
| LiveBench research | 43.5% | Not measured | Only GPT-6 Luna measured |
| LiveBench browser | 72.0% | Not measured | Only GPT-6 Luna measured |
| LiveBench long agentic | 48.1% | Not measured | Only GPT-6 Luna measured |
| SREBench (Vals AI) | 2.7% | Not measured | Only GPT-6 Luna measured |
| Finance Agent (Vals AI) | 49.9% | 41.5% | GPT-6 Luna |
| Tax Agent Bench (Vals AI) | 19.9% | 11.5% | GPT-6 Luna |
| Legal Research Bench (Vals AI) | 30.3% | 15.9% | GPT-6 Luna |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | Not measured | Only GPT-6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | 68.5% | 55.2% | GPT-6 Luna |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only GPT-6 Luna measured |
| Vals Science Index | 28.4% | Not measured | Only GPT-6 Luna measured |
| τ²-Bench Telecom | Not measured | 94.2% | Only MiMo-V2.5-Pro measured |
| APEX-Agents | 44.3% | Not measured | Only GPT-6 Luna measured |
| SpireClimb | 0.0% | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.6% | Only MiMo-V2.5-Pro measured |
| LiveBench reasoning | 81.8% | Not measured | Only GPT-6 Luna measured |
| MysteryMechanism (Vals AI) | 19.4% | Not measured | Only GPT-6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 86.6% | Only MiMo-V2.5-Pro measured |
| Humanity's Last Exam (Artificial Analysis run) | 38.5% | 35.7% | GPT-6 Luna |
| GPQA Diamond (Epoch AI run) | 90.5% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI | 86.7% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI-2 | 59.3% | Not measured | Only GPT-6 Luna measured |
| Chess puzzles | 36.0% | Not measured | Only GPT-6 Luna measured |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: hard prompts | 1410 | 1486 | MiMo-V2.5-Pro |
| LMArena Text: expert | 1442 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: hard prompts in English | 1410 | 1494 | MiMo-V2.5-Pro |
| LMArena Vision: diagrams | 1245 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: homework | 1261 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tiers 1 to 3 | 78.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tier 4 | 56.1% | Not measured | Only GPT-6 Luna measured |
| ProofBench | 64.0% | 22.0% | GPT-6 Luna |
| LMArena Text: math | 1409 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: mathematical work | 1427 | 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 index14
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.6% | Only MiMo-V2.5-Pro measured |
| LegalBench (Vals AI) | Not measured | 77.1% | Only MiMo-V2.5-Pro measured |
| CorpFin (Vals AI) | Not measured | 61.4% | Only MiMo-V2.5-Pro measured |
| TaxEval (Vals AI) | Not measured | 73.8% | Only MiMo-V2.5-Pro measured |
| MedCode (Vals AI) | 44.7% | 32.5% | GPT-6 Luna |
| SimpleQA Verified | 41.4% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: science | 1386 | 1482 | MiMo-V2.5-Pro |
| LMArena Text: medicine and healthcare | 1352 | 1473 | MiMo-V2.5-Pro |
| LMArena Text: legal and government | 1400 | 1474 | MiMo-V2.5-Pro |
| LMArena Text: business and finance | 1388 | 1466 | MiMo-V2.5-Pro |
| FACTS Benchmark Suite | 63.3% | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1271 | 1266 | GPT-6 Luna |
| Design Arena: UI components | 1295 | 1246 | GPT-6 Luna |
| Design Arena: game dev | 1257 | 1261 | MiMo-V2.5-Pro |
| Design Arena: data viz | 1216 | 1257 | MiMo-V2.5-Pro |
| Design Arena: 3D | 1218 | 1243 | MiMo-V2.5-Pro |
| Design Arena: all code categories | 1270 | 1265 | GPT-6 Luna |
| Design Arena: SVG | 1252 | 1181 | GPT-6 Luna |
| Design Arena: ASCII art | 1153 | 1156 | MiMo-V2.5-Pro |
| LiveBench design | 82.5% | Not measured | Only GPT-6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index318
| Benchmark | GPT-6 Luna | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Vals Index | 52.3% | Not measured | Only GPT-6 Luna measured |
| LiveBench data analysis | 73.4% | Not measured | Only GPT-6 Luna measured |
| Public Benefits Bench (Vals AI) | 57.6% | Not measured | Only GPT-6 Luna measured |
| SAGE (Vals AI) | 48.1% | Not measured | Only GPT-6 Luna measured |
| MedScribe (Vals AI) | 83.7% | 83.7% | MiMo-V2.5-Pro |
| IFBench | Not measured | 79.9% | Only MiMo-V2.5-Pro measured |
| Long context reasoning (AA-LCR) | 83.3% | 79.7% | GPT-6 Luna |
| DTBench | 90.1% | 84.5% | GPT-6 Luna |
| LMCA | 44.5% | 29.5% | GPT-6 Luna |
| Furniture assembly | 44.2% | Not measured | Only GPT-6 Luna measured |
| LMArena Text | 1389 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: instruction following | 1408 | 1475 | MiMo-V2.5-Pro |
| LMArena Text: creative writing | 1363 | 1438 | MiMo-V2.5-Pro |
| LMArena Vision | 1216 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: English | 1393 | 1477 | MiMo-V2.5-Pro |
| LMArena Text: non-English | 1381 | 1448 | MiMo-V2.5-Pro |
| LMArena Text: Chinese | 1427 | 1507 | MiMo-V2.5-Pro |
| LMArena Text: German | 1376 | 1459 | MiMo-V2.5-Pro |
| LMArena Text: Japanese | 1369 | 1410 | MiMo-V2.5-Pro |
| LMArena Text: Korean | 1359 | 1435 | MiMo-V2.5-Pro |
| LMArena Text: French | 1408 | 1487 | MiMo-V2.5-Pro |
| LMArena Text: Spanish | 1391 | 1469 | MiMo-V2.5-Pro |
| LMArena Text: Russian | 1392 | 1449 | MiMo-V2.5-Pro |
| LMArena Text: Polish | 1383 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: multi-turn | 1392 | 1476 | MiMo-V2.5-Pro |
| LMArena Text: longer queries | 1408 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: writing and language | 1384 | 1451 | MiMo-V2.5-Pro |
| LMArena Text: entertainment and media | 1364 | 1438 | MiMo-V2.5-Pro |
| LMArena Vision: English | 1204 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: Chinese | 1266 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: reading text | 1225 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: creative writing | 1205 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-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
GPT-6 Luna costs less
Repository review
50K input + 3K output tokens
GPT-6 Luna costs less
Agent loop
200K input + 10K output tokens
GPT-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-6 Luna | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | September 22, 2026 | April 22, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.10 | $0.4575 |
| Output $/Mtok | $0.50 | $0.9152 |
| Coding index | 57.3 | 31.6 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | Not computable | $0.03 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Luna better than MiMo-V2.5-Pro for coding?
Pick GPT-6 Luna for coding: it scores 57.3 on the Vibe Coding Index against 31.6 for MiMo-V2.5-Pro. Pick MiMo-V2.5-Pro for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, GPT-6 Luna or MiMo-V2.5-Pro?
GPT-6 Luna costs $0.10 per million input tokens and $0.50 per million output tokens; MiMo-V2.5-Pro costs $0.4575 and $0.9152. Cost per solved task is known for MiMo-V2.5-Pro only.
Which has the bigger context window, GPT-6 Luna or MiMo-V2.5-Pro?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-6 Luna vs MiMo-V2.5-Pro comparison based on?
57 benchmarks have a result for both models as of October 22, 2026. GPT-6 Luna's coding index rests on 5 independent benchmarks and MiMo-V2.5-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.