GPT-5.6 Sol vs MiMo-V2.6-Pro
Updated October 21, 2026. 69 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 Sol for coding: it scores 76.7 on the Vibe Coding Index against 72.6 for MiMo-V2.6-Pro.
Pick MiMo-V2.6-Pro when output tokens cost 23.0x less, or when what matters is LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
- Shared results
- 69
- GPT-5.6 Sol only
- 67
- MiMo-V2.6-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 Sol
GPT-5.6 Sol scores 76.7 against 72.6.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 47.0 against 46.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Sol has a AA Agentic Index result, 50.2.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Sol has a GPQA Diamond result, 95.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Sol has a MMLU Pro result, 89.1%.
Directional only
Web design
Design Arena: websites
GPT-5.6 Sol
GPT-5.6 Sol leads, 1321 against 1308.
Same board, both measured
General
Vals Index
No call
Only MiMo-V2.6-Pro has a Vals Index result, 57.8%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
GPT-5.6 Sol $0.014, MiMo-V2.6-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Sol has the number, $1.20.
Directional only
At a glance
- Coding index
- GPT-5.6 Sol 76.7 from 2 benchmarks, MiMo-V2.6-Pro 72.6 from 2 benchmarks.
- Widest category
- Coding, 9.7 points apart on average over 16 shared benchmarks.
- Widest single gap
- IOI (Vals AI): GPT-5.6 Sol 91.2% against MiMo-V2.6-Pro 39.3%, 51.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Sol $20.00 against MiMo-V2.6-Pro $0.87 per million output tokens, 23.0x 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 Sol | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 10 | 6 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 5 | 4 | 1 tie | |
| Reasoning | 5 | 3 | ||
| Math | 1 | 2 | ||
| Knowledge | 0 | 5 | ||
| Web design | 5 | 1 | 1 tie | |
| General | 5 | 14 | ||
| All shared boards | 32 | 35 | 2 ties |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index106
| Benchmark | GPT-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | 89.7% | 81.5% | GPT-5.6 Sol |
| LMArena WebDev | 1616 | 1625 | MiMo-V2.6-Pro |
| AA Coding Index | 77.4 | Not measured | Only GPT-5.6 Sol measured |
| LiveCodeBench (Vals AI) | 82.6% | Not measured | Only GPT-5.6 Sol measured |
| SWE-bench Verified (Vals AI) | 96.2% | Not measured | Only GPT-5.6 Sol measured |
| Terminal-Bench 4 (Vals AI) | 37.9% | 31.3% | GPT-5.6 Sol |
| Vibe Code Bench (Vals AI) | 80.5% | 85.2% | MiMo-V2.6-Pro |
| Code migration (Vals AI) | 52.9% | 43.0% | GPT-5.6 Sol |
| ProgramBench (Vals AI) | 1.5% | 0.5% | GPT-5.6 Sol |
| IOI (Vals AI) | 91.2% | 39.3% | GPT-5.6 Sol |
| Terminal-Bench 2.1 (Vals AI) | 85.8% | 67.8% | GPT-5.6 Sol |
| SWE-bench Multimodal (Vals AI) | Not measured | 41.3% | Only MiMo-V2.6-Pro measured |
| Vibe Code Bench 1-100 (Vals AI) | 20.0% | Not measured | Only GPT-5.6 Sol measured |
| SkillsBench (Vals AI) | 54.1% | Not measured | Only GPT-5.6 Sol measured |
| CyberBench (Vals AI) | 76.3% | 72.9% | GPT-5.6 Sol |
| SciCode | 57.8% | 60.9% | MiMo-V2.6-Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 65.9% | Not measured | Only GPT-5.6 Sol measured |
| FrontierCode | 47.5% | Not measured | Only GPT-5.6 Sol measured |
| FrontierSWE | 32.2% | Not measured | Only GPT-5.6 Sol measured |
| GSO-Bench | 76.5% | Not measured | Only GPT-5.6 Sol measured |
| WeirdML | 88.8% | Not measured | Only GPT-5.6 Sol measured |
| MirrorCode | 20.0% | Not measured | Only GPT-5.6 Sol measured |
| ALE-Bench | 2176.9 | 1158.1 | GPT-5.6 Sol |
| LMArena Text: coding | 1496 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1489 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1620 | 1639 | MiMo-V2.6-Pro |
| LMArena WebDev: HTML | 1618 | 1616 | GPT-5.6 Sol |
| LMArena WebDev: from an image | 1609 | 1598 | GPT-5.6 Sol |
| Neither model has a result on the other 10 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 47.0 | 46.3 | GPT-5.6 Sol |
| Epoch Capabilities Index | 162.8 | Not measured | Only GPT-5.6 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index54
| Benchmark | GPT-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 50.2 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building web apps | 1245 | 1291 | MiMo-V2.6-Pro |
| Design Arena: agents building full-stack apps | 1261 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building mobile apps | 1249 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building Android apps | 1246 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building Godot games | 1260 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building games | 1267 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: HTML slides | 1286 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: PowerPoint slides | 1240 | Not measured | Only GPT-5.6 Sol measured |
| LiveBench research | 54.5% | 76.7% | MiMo-V2.6-Pro |
| LiveBench browser | 88.0% | 88.0% | Tie |
| LiveBench long agentic | 48.5% | 47.5% | GPT-5.6 Sol |
| SREBench (Vals AI) | 30.5% | 3.0% | GPT-5.6 Sol |
| Finance Agent (Vals AI) | 53.8% | 57.3% | MiMo-V2.6-Pro |
| Tax Agent Bench (Vals AI) | 31.1% | 32.4% | MiMo-V2.6-Pro |
| Legal Research Bench (Vals AI) | 48.1% | 47.1% | GPT-5.6 Sol |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.8% | Only MiMo-V2.6-Pro measured |
| Excel Modeling Benchmark (Vals AI) | 72.3% | 62.9% | GPT-5.6 Sol |
| BioMysteryBench (Vals AI) | 71.1% | Not measured | Only GPT-5.6 Sol measured |
| Terminal-Bench-Science (Vals AI) | 20.0% | 2.9% | GPT-5.6 Sol |
| Vals Science Index | 41.5% | Not measured | Only GPT-5.6 Sol measured |
| Time Horizon Index (Vals AI) | 23.8% | Not measured | Only GPT-5.6 Sol measured |
| CUA-bench (Vals AI) | 8.3% | Not measured | Only GPT-5.6 Sol measured |
| τ²-Bench Telecom | 85.1% | Not measured | Only GPT-5.6 Sol measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| OSWorld 2.0 | 27.3% | Not measured | Only GPT-5.6 Sol measured |
| BALROG | 60.0% | Not measured | Only GPT-5.6 Sol measured |
| PostTrainBench | 36.2% | Not measured | Only GPT-5.6 Sol measured |
| Vending-Bench 2 | $9,619 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Search | 1261 | Not measured | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 9 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index53
| Benchmark | GPT-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 95.2% | Not measured | Only GPT-5.6 Sol measured |
| LiveBench reasoning | 91.7% | 79.6% | GPT-5.6 Sol |
| MysteryMechanism (Vals AI) | 33.3% | 15.3% | GPT-5.6 Sol |
| MMMU Pro (Vals AI) | 88.8% | Not measured | Only GPT-5.6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 94.1% | Not measured | Only GPT-5.6 Sol measured |
| Humanity's Last Exam (Artificial Analysis run) | 49.5% | 49.4% | GPT-5.6 Sol |
| GPQA Diamond (Epoch AI run) | 93.5% | Not measured | Only GPT-5.6 Sol measured |
| ARC-AGI | 97.5% | Not measured | Only GPT-5.6 Sol measured |
| ARC-AGI-2 | 92.5% | Not measured | Only GPT-5.6 Sol measured |
| SimpleBench | 64.8% | Not measured | Only GPT-5.6 Sol measured |
| Chess puzzles | 59.0% | Not measured | Only GPT-5.6 Sol measured |
| Mystery game puzzles | 58.0% | Not measured | Only GPT-5.6 Sol measured |
| EBR-bench | 44.8% | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts | 1483 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1517 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1477 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1305 | 1281 | GPT-5.6 Sol |
| LMArena Vision: homework | 1305 | 1264 | GPT-5.6 Sol |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-5.6 Sol measured |
| FrontierMath, tiers 1 to 3 | 89.1% | Not measured | Only GPT-5.6 Sol measured |
| FrontierMath, tier 4 | 82.9% | Not measured | Only GPT-5.6 Sol measured |
| ProofBench | 83.0% | 70.0% | GPT-5.6 Sol |
| LMArena Text: math | 1473 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1496 | 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-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MMLU Pro | 89.1% | Not measured | Only GPT-5.6 Sol measured |
| LegalBench (Vals AI) | 87.0% | Not measured | Only GPT-5.6 Sol measured |
| CorpFin (Vals AI) | 64.4% | Not measured | Only GPT-5.6 Sol measured |
| TaxEval (Vals AI) | 74.8% | Not measured | Only GPT-5.6 Sol measured |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Sol measured |
| MedCode (Vals AI) | 44.0% | 45.0% | MiMo-V2.6-Pro |
| SimpleQA Verified | 69.7% | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: science | 1455 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1431 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1476 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1457 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | GPT-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1321 | 1308 | GPT-5.6 Sol |
| Design Arena: UI components | 1338 | 1338 | Tie |
| Design Arena: game dev | 1368 | 1314 | GPT-5.6 Sol |
| Design Arena: data viz | 1323 | 1337 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1385 | 1330 | GPT-5.6 Sol |
| Design Arena: all code categories | 1341 | 1317 | GPT-5.6 Sol |
| Design Arena: SVG | 1316 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: ASCII art | 1302 | Not measured | Only GPT-5.6 Sol measured |
| LiveBench design | 81.6% | 78.5% | GPT-5.6 Sol |
GeneralLike-for-likePublic boards, shown as published, kept out of the index514
| Benchmark | GPT-5.6 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 57.8% | Only MiMo-V2.6-Pro measured |
| LiveBench data analysis | 79.8% | 72.3% | GPT-5.6 Sol |
| Public Benefits Bench (Vals AI) | 66.5% | 68.9% | MiMo-V2.6-Pro |
| SAGE (Vals AI) | 52.6% | 45.0% | GPT-5.6 Sol |
| MedScribe (Vals AI) | 85.2% | 88.3% | MiMo-V2.6-Pro |
| Vals Multimodal Index | 72.6% | Not measured | Only GPT-5.6 Sol measured |
| IFBench | 72.7% | Not measured | Only GPT-5.6 Sol measured |
| Long context reasoning (AA-LCR) | 84.0% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 95.7% | Not measured | Only GPT-5.6 Sol measured |
| LMCA | 58.5% | Not measured | Only GPT-5.6 Sol measured |
| Surface Evolver Bench | 93.1% | Not measured | Only GPT-5.6 Sol measured |
| Furniture assembly | 56.7% | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text | 1457 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1483 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1449 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1281 | 1263 | GPT-5.6 Sol |
| LMArena Text: English | 1457 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1451 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1525 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: German | 1476 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Japanese | 1472 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Korean | 1442 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: French | 1472 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Spanish | 1443 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Russian | 1471 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: Polish | 1459 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: multi-turn | 1461 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1481 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1462 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1450 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1280 | 1268 | GPT-5.6 Sol |
| LMArena Vision: Chinese | 1313 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: reading text | 1290 | 1270 | GPT-5.6 Sol |
| LMArena Vision: humor | 1246 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: creative writing | 1283 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Document | 1483 | Not measured | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Sol | 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
MiMo-V2.6-Pro costs less
Repository review
50K input + 3K output tokens
MiMo-V2.6-Pro costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.6-Pro 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 Sol | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | September 21, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $4.00 | $0.435 |
| Output $/Mtok | $20.00 | $0.87 |
| Coding index | 76.7 | 72.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $1.20 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Sol better than MiMo-V2.6-Pro for coding?
Pick GPT-5.6 Sol for coding: it scores 76.7 on the Vibe Coding Index against 72.6 for MiMo-V2.6-Pro. Pick MiMo-V2.6-Pro when output tokens cost 23.0x less, or when what matters is LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, GPT-5.6 Sol or MiMo-V2.6-Pro?
GPT-5.6 Sol costs $4.00 per million input tokens and $20.00 per million output tokens; MiMo-V2.6-Pro costs $0.435 and $0.87. Cost per solved task is known for GPT-5.6 Sol only.
Which has the bigger context window, GPT-5.6 Sol or MiMo-V2.6-Pro?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-5.6 Sol vs MiMo-V2.6-Pro comparison based on?
69 benchmarks have a result for both models as of October 21, 2026. GPT-5.6 Sol'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.