GPT-6 Luna vs MiMo-V2.6-Pro
Updated October 21, 2026. 73 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
GPT-6 Luna and MiMo-V2.6-Pro are level for coding, 71.4 against 72.6 on the Vibe Coding Index, so price and context decide.
Pick GPT-6 Luna when output tokens cost 1.7x less, or when what matters is LiveBench coding or IOI (Vals AI), where it leads. Pick MiMo-V2.6-Pro when what matters is LMArena WebDev or Terminal-Bench 4 (Vals AI), where it leads.
- Shared results
- 73
- GPT-6 Luna only
- 29
- MiMo-V2.6-Pro only
- 0
- 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
No call
Level: 71.4 against 72.6, inside 2 points.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 38.1.
Same board, both measured
Web design
Design Arena: websites
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 1308 against 1272.
Same board, both measured
General
Vals Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 57.8% against 52.3%.
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
GPT-6 Luna
GPT-6 Luna $0.0003, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- GPT-6 Luna 71.4 from 2 benchmarks, MiMo-V2.6-Pro 72.6 from 2 benchmarks.
- Widest category
- Knowledge, 14.3 points apart on average over 5 shared benchmarks.
- Widest single gap
- LiveBench research: GPT-6 Luna 43.5% against MiMo-V2.6-Pro 76.7%, 33.2 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Luna $0.50 against MiMo-V2.6-Pro $0.87 per million output tokens, 1.7x 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-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 5 | 11 | 1 tie | |
| Intelligence | 0 | 1 | ||
| Agentic work | 3 | 9 | ||
| Reasoning | 2 | 6 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 5 | ||
| Web design | 1 | 6 | ||
| General | 2 | 18 | ||
| All shared boards | 13 | 59 | 1 tie |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index511
| Benchmark | GPT-6 Luna | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | 81.5% | GPT-6 Luna |
| LMArena WebDev | 1578 | 1625 | MiMo-V2.6-Pro |
| Terminal-Bench 4 (Vals AI) | 13.6% | 31.3% | MiMo-V2.6-Pro |
| Vibe Code Bench (Vals AI) | 81.7% | 85.2% | MiMo-V2.6-Pro |
| Code migration (Vals AI) | 42.5% | 43.0% | MiMo-V2.6-Pro |
| ProgramBench (Vals AI) | 0.5% | 0.5% | Tie |
| IOI (Vals AI) | 55.6% | 39.3% | GPT-6 Luna |
| Terminal-Bench 2.1 (Vals AI) | 73.0% | 67.8% | GPT-6 Luna |
| SWE-bench Multimodal (Vals AI) | 37.5% | 41.3% | MiMo-V2.6-Pro |
| CyberBench (Vals AI) | 76.3% | 72.9% | GPT-6 Luna |
| SciCode | 54.6% | 60.9% | MiMo-V2.6-Pro |
| FrontierCode | 42.4% | Not measured | Only GPT-6 Luna measured |
| ALE-Bench | 1576.9 | 1158.1 | GPT-6 Luna |
| LMArena Text: coding | 1437 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1423 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1573 | 1639 | MiMo-V2.6-Pro |
| LMArena WebDev: HTML | 1595 | 1616 | MiMo-V2.6-Pro |
| LMArena WebDev: from an image | 1571 | 1598 | MiMo-V2.6-Pro |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-6 Luna | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.1 | 46.3 | MiMo-V2.6-Pro |
| Epoch Capabilities Index | 156.8 | Not measured | Only GPT-6 Luna measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index39
| Benchmark | GPT-6 Luna | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1189 | 1291 | MiMo-V2.6-Pro |
| Design Arena: agents building full-stack apps | 1158 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building mobile apps | 1133 | Not measured | Only GPT-6 Luna measured |
| LiveBench research | 43.5% | 76.7% | MiMo-V2.6-Pro |
| LiveBench browser | 72.0% | 88.0% | MiMo-V2.6-Pro |
| LiveBench long agentic | 48.1% | 47.5% | GPT-6 Luna |
| SREBench (Vals AI) | 2.7% | 3.0% | MiMo-V2.6-Pro |
| Finance Agent (Vals AI) | 49.9% | 57.3% | MiMo-V2.6-Pro |
| Tax Agent Bench (Vals AI) | 19.9% | 32.4% | MiMo-V2.6-Pro |
| Legal Research Bench (Vals AI) | 30.3% | 47.1% | MiMo-V2.6-Pro |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | 13.8% | MiMo-V2.6-Pro |
| Excel Modeling Benchmark (Vals AI) | 68.5% | 62.9% | GPT-6 Luna |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | 2.9% | GPT-6 Luna |
| Vals Science Index | 28.4% | Not measured | Only GPT-6 Luna measured |
| APEX-Agents | 44.3% | 54.4% | MiMo-V2.6-Pro |
| 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 index26
| Benchmark | GPT-6 Luna | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench reasoning | 81.8% | 79.6% | GPT-6 Luna |
| MysteryMechanism (Vals AI) | 19.4% | 15.3% | GPT-6 Luna |
| Humanity's Last Exam (Artificial Analysis run) | 38.5% | 49.4% | MiMo-V2.6-Pro |
| 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 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1442 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1410 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1245 | 1281 | MiMo-V2.6-Pro |
| LMArena Vision: homework | 1261 | 1264 | MiMo-V2.6-Pro |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-6 Luna | MiMo-V2.6-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% | 70.0% | MiMo-V2.6-Pro |
| LMArena Text: math | 1409 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1427 | 1511 | MiMo-V2.6-Pro |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | GPT-6 Luna | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 44.7% | 45.0% | MiMo-V2.6-Pro |
| SimpleQA Verified | 41.4% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: science | 1386 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1352 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1400 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1388 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | GPT-6 Luna | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1272 | 1308 | MiMo-V2.6-Pro |
| Design Arena: UI components | 1297 | 1338 | MiMo-V2.6-Pro |
| Design Arena: game dev | 1259 | 1314 | MiMo-V2.6-Pro |
| Design Arena: data viz | 1215 | 1337 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1217 | 1330 | MiMo-V2.6-Pro |
| Design Arena: all code categories | 1271 | 1317 | MiMo-V2.6-Pro |
| Design Arena: SVG | 1253 | Not measured | Only GPT-6 Luna measured |
| Design Arena: ASCII art | 1156 | Not measured | Only GPT-6 Luna measured |
| LiveBench design | 82.5% | 78.5% | GPT-6 Luna |
GeneralLike-for-likePublic boards, shown as published, kept out of the index218
| Benchmark | GPT-6 Luna | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | 52.3% | 57.8% | MiMo-V2.6-Pro |
| LiveBench data analysis | 73.4% | 72.3% | GPT-6 Luna |
| Public Benefits Bench (Vals AI) | 57.6% | 68.9% | MiMo-V2.6-Pro |
| SAGE (Vals AI) | 48.1% | 45.0% | GPT-6 Luna |
| MedScribe (Vals AI) | 83.7% | 88.3% | MiMo-V2.6-Pro |
| Long context reasoning (AA-LCR) | 83.3% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 90.1% | Not measured | Only GPT-6 Luna measured |
| LMCA | 44.5% | Not measured | Only GPT-6 Luna measured |
| Furniture assembly | 44.2% | Not measured | Only GPT-6 Luna measured |
| LMArena Text | 1389 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1408 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1363 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1216 | 1263 | MiMo-V2.6-Pro |
| LMArena Text: English | 1393 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1381 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1427 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: German | 1376 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Japanese | 1369 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Korean | 1359 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: French | 1408 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Spanish | 1391 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Russian | 1392 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: Polish | 1383 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: multi-turn | 1392 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1408 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1384 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1364 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1204 | 1268 | MiMo-V2.6-Pro |
| LMArena Vision: Chinese | 1266 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: reading text | 1225 | 1270 | MiMo-V2.6-Pro |
| LMArena Vision: creative writing | 1205 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Luna | MiMo-V2.6-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-V2.6-Pro |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | September 22, 2026 | September 21, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.10 | $0.435 |
| Output $/Mtok | $0.50 | $0.87 |
| Coding index | 71.4 | 72.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Luna better than MiMo-V2.6-Pro for coding?
GPT-6 Luna and MiMo-V2.6-Pro are level for coding, 71.4 against 72.6 on the Vibe Coding Index, so price and context decide. Pick GPT-6 Luna when output tokens cost 1.7x less, or when what matters is LiveBench coding or IOI (Vals AI), where it leads. Pick MiMo-V2.6-Pro when what matters is LMArena WebDev or Terminal-Bench 4 (Vals AI), where it leads.
Which is cheaper, GPT-6 Luna or MiMo-V2.6-Pro?
GPT-6 Luna costs $0.10 per million input tokens and $0.50 per million output tokens; MiMo-V2.6-Pro costs $0.435 and $0.87. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Luna or MiMo-V2.6-Pro?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-6 Luna vs MiMo-V2.6-Pro comparison based on?
73 benchmarks have a result for both models as of October 21, 2026. GPT-6 Luna's coding index rests on 2 independent benchmarks and MiMo-V2.6-Pro's on 2. Where only one model has a result, the page says so instead of naming a winner.