GPT-6.1 Sol vs MiMo-V2.6-Pro
GPT-6.1 Sol leads MiMo-V2.6-Pro on coding, 82.4 to 65.4 on the Vibe Coding Index, and MiMo-V2.6-Pro costs 11.5x less per output token ($0.87 vs $10.00 per million). Updated October 22, 2026; 72 benchmarks have a result for both.
GPT-6.1 Sol or MiMo-V2.6-Pro: which to pick
Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 65.4 for MiMo-V2.6-Pro.
Pick MiMo-V2.6-Pro for output tokens 11.5x cheaper ($0.87 vs $10.00 per million) and work measured by CyberBench (Vals AI) or SciCode, where it leads.
- Shared results
- 72
- GPT-6.1 Sol only
- 26
- MiMo-V2.6-Pro only
- 1
- 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-6.1 Sol
GPT-6.1 Sol scores 82.4 against 65.4.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 51.8 against 46.3.
Same board, both measured
Web design
Design Arena: websites
GPT-6.1 Sol
GPT-6.1 Sol leads, 1321 against 1308.
Same board, both measured
General
Vals Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 63.9% against 57.8%.
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-V2.6-Pro
GPT-6.1 Sol $0.0070, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- GPT-6.1 Sol 82.4 from 5 benchmarks, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Coding, 16.4 points apart on average over 16 shared benchmarks.
- Widest single gap
- IOI (Vals AI): GPT-6.1 Sol 96.9% against MiMo-V2.6-Pro 39.3%, 57.6 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Sol $10.00 against MiMo-V2.6-Pro $0.87 per million output tokens, 11.5x 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-6.1 Sol | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 12 | 4 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 7 | 4 | 1 tie | |
| Reasoning | 5 | 3 | ||
| Math | 2 | 1 | ||
| Knowledge | 1 | 4 | ||
| Web design | 5 | 2 | ||
| General | 6 | 14 | ||
| All shared boards | 39 | 32 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index124
| Benchmark | GPT-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | 96.0% | 81.5% | GPT-6.1 Sol |
| LMArena WebDev | 1753 | 1625 | GPT-6.1 Sol |
| Terminal-Bench 4 (Vals AI) | 55.0% | 31.3% | GPT-6.1 Sol |
| Vibe Code Bench (Vals AI) | 88.9% | 85.2% | GPT-6.1 Sol |
| Code migration (Vals AI) | 65.1% | 43.0% | GPT-6.1 Sol |
| ProgramBench (Vals AI) | 3.0% | 0.5% | GPT-6.1 Sol |
| IOI (Vals AI) | 96.9% | 39.3% | GPT-6.1 Sol |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.8% | Only MiMo-V2.6-Pro measured |
| SWE-bench Multimodal (Vals AI) | 43.5% | 41.3% | GPT-6.1 Sol |
| CyberBench (Vals AI) | 39.3% | 72.9% | MiMo-V2.6-Pro |
| SciCode | 55.8% | 60.9% | MiMo-V2.6-Pro |
| FrontierCode | 50.2% | Not measured | Only GPT-6.1 Sol measured |
| ALE-Bench | 2743.8 | 1158.1 | GPT-6.1 Sol |
| LMArena Text: coding | 1478 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1476 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1754 | 1639 | GPT-6.1 Sol |
| LMArena WebDev: HTML | 1800 | 1616 | GPT-6.1 Sol |
| LMArena WebDev: from an image | 1702 | 1598 | GPT-6.1 Sol |
| SciCode | 9.2% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.8 | 46.3 | GPT-6.1 Sol |
| Epoch Capabilities Index | 168.4 | Not measured | Only GPT-6.1 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index74
| Benchmark | GPT-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1306 | 1290 | GPT-6.1 Sol |
| Design Arena: agents building mobile apps | 1213 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: spreadsheets | 1259 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench research | 83.5% | 76.7% | GPT-6.1 Sol |
| LiveBench browser | 88.0% | 88.0% | Tie |
| LiveBench long agentic | 73.0% | 47.5% | GPT-6.1 Sol |
| SREBench (Vals AI) | 50.8% | 3.0% | GPT-6.1 Sol |
| Finance Agent (Vals AI) | 52.0% | 57.3% | MiMo-V2.6-Pro |
| Tax Agent Bench (Vals AI) | 21.8% | 32.4% | MiMo-V2.6-Pro |
| Legal Research Bench (Vals AI) | 38.5% | 47.1% | MiMo-V2.6-Pro |
| Harvey's Legal Agent Benchmark (Vals AI) | 6.3% | 13.8% | MiMo-V2.6-Pro |
| Excel Modeling Benchmark (Vals AI) | 70.8% | 62.9% | GPT-6.1 Sol |
| BioMysteryBench (Vals AI) | 79.6% | Not measured | Only GPT-6.1 Sol measured |
| Terminal-Bench-Science (Vals AI) | 52.9% | 2.9% | GPT-6.1 Sol |
| Vals Science Index | 59.6% | Not measured | Only GPT-6.1 Sol measured |
| Robo-bench (Vals AI) | 28.3% | Not measured | Only GPT-6.1 Sol measured |
| APEX-Agents | 60.0% | 54.4% | GPT-6.1 Sol |
| SpireClimb | 24.7% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index53
| Benchmark | GPT-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.6% | 79.6% | GPT-6.1 Sol |
| MysteryMechanism (Vals AI) | 46.4% | 15.3% | GPT-6.1 Sol |
| Humanity's Last Exam (Artificial Analysis run) | 52.9% | 49.4% | GPT-6.1 Sol |
| GPQA Diamond (Epoch AI run) | 95.4% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI | 98.5% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI-2 | 94.2% | Not measured | Only GPT-6.1 Sol measured |
| Chess puzzles | 68.0% | Not measured | Only GPT-6.1 Sol measured |
| Mystery game puzzles | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| EBR-bench | 54.3% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts | 1463 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1489 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1465 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1306 | 1281 | GPT-6.1 Sol |
| LMArena Vision: homework | 1356 | 1264 | GPT-6.1 Sol |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | GPT-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tiers 1 to 3 | 93.7% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tier 4 | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| ProofBench | 99.0% | 70.0% | GPT-6.1 Sol |
| LMArena Text: math | 1489 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1513 | 1511 | GPT-6.1 Sol |
| 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-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 48.8% | 45.0% | GPT-6.1 Sol |
| SimpleQA Verified | 73.9% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: science | 1444 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1433 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1471 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1445 | 1468 | MiMo-V2.6-Pro |
| FACTS Benchmark Suite | 75.3% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index52
| Benchmark | GPT-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1321 | 1308 | GPT-6.1 Sol |
| Design Arena: UI components | 1317 | 1340 | MiMo-V2.6-Pro |
| Design Arena: game dev | 1389 | 1314 | GPT-6.1 Sol |
| Design Arena: data viz | 1281 | 1336 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1460 | 1330 | GPT-6.1 Sol |
| Design Arena: all code categories | 1345 | 1317 | GPT-6.1 Sol |
| LiveBench design | 82.1% | 78.5% | GPT-6.1 Sol |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index614
| Benchmark | GPT-6.1 Sol | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | 63.9% | 57.8% | GPT-6.1 Sol |
| LiveBench data analysis | 82.7% | 72.3% | GPT-6.1 Sol |
| Public Benefits Bench (Vals AI) | 59.3% | 68.9% | MiMo-V2.6-Pro |
| SAGE (Vals AI) | 46.5% | 45.0% | GPT-6.1 Sol |
| MedScribe (Vals AI) | 86.5% | 88.3% | MiMo-V2.6-Pro |
| Long context reasoning (AA-LCR) | 84.0% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 96.5% | Not measured | Only GPT-6.1 Sol measured |
| LMCA | 62.8% | Not measured | Only GPT-6.1 Sol measured |
| Furniture assembly | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text | 1443 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1466 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1425 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1288 | 1263 | GPT-6.1 Sol |
| LMArena Text: English | 1450 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1433 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1487 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: French | 1460 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Spanish | 1439 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Russian | 1457 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: multi-turn | 1442 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1458 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1444 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1426 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1274 | 1268 | GPT-6.1 Sol |
| LMArena Vision: reading text | 1289 | 1270 | GPT-6.1 Sol |
| LMArena Vision: creative writing | 1301 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 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-6.1 Sol | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | September 29, 2026 | September 21, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $0.435 |
| Output $/Mtok | $10.00 | $0.87 |
| Coding index | 82.4 | 65.4 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Sol better than MiMo-V2.6-Pro for coding?
Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 65.4 for MiMo-V2.6-Pro. Pick MiMo-V2.6-Pro for output tokens 11.5x cheaper ($0.87 vs $10.00 per million) and work measured by CyberBench (Vals AI) or SciCode, where it leads.
Which is cheaper, GPT-6.1 Sol or MiMo-V2.6-Pro?
GPT-6.1 Sol costs $2.00 per million input tokens and $10.00 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-6.1 Sol or MiMo-V2.6-Pro?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-6.1 Sol vs MiMo-V2.6-Pro comparison based on?
72 benchmarks have a result for both models as of October 22, 2026. GPT-6.1 Sol's coding index rests on 5 independent benchmarks and MiMo-V2.6-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.