Gemini 2.5 Pro vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads Gemini 2.5 Pro on coding, 65.4 to 19.1 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 21, 2026; 44 benchmarks have a result for both.
Gemini 2.5 Pro or MiMo-V2.6-Pro: which to pick
Pick MiMo-V2.6-Pro for coding: it scores 65.4 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro.
Pick Gemini 2.5 Pro for work measured by LMArena Vision: homework or MedCode (Vals AI), where it leads.
- Shared results
- 44
- Gemini 2.5 Pro only
- 46
- MiMo-V2.6-Pro only
- 29
- Like-for-like categories
- 7 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
MiMo-V2.6-Pro
MiMo-V2.6-Pro scores 65.4 against 19.1.
3 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 2.5 Pro has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 1308 against 1167.
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
MiMo-V2.6-Pro
MiMo-V2.6-Pro takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
Gemini 2.5 Pro $0.0063, MiMo-V2.6-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Pro has the number, $0.64.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Coding, 42.1 points apart on average over 7 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 2.5 Pro 0.4% against MiMo-V2.6-Pro 85.2%, 84.8 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against MiMo-V2.6-Pro $0.87 per million output tokens, 11.5x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, MiMo-V2.6-Pro 1.05M.
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 | Gemini 2.5 Pro | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 1 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 1 | 4 | ||
| Web design | 0 | 6 | ||
| General | 2 | 15 | ||
| All shared boards | 4 | 40 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LiveBench coding | Not measured | 81.5% | Only MiMo-V2.6-Pro measured |
| LMArena WebDev | 1226 | 1625 | MiMo-V2.6-Pro |
| AA Coding Index | 33.3 | Not measured | Only Gemini 2.5 Pro measured |
| SWE-bench Verified (Vals AI) | 54.4% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.3% | Only MiMo-V2.6-Pro measured |
| Vibe Code Bench (Vals AI) | 0.4% | 85.2% | MiMo-V2.6-Pro |
| Code migration (Vals AI) | Not measured | 43.0% | Only MiMo-V2.6-Pro measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only MiMo-V2.6-Pro measured |
| IOI (Vals AI) | Not measured | 39.3% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.8% | Only MiMo-V2.6-Pro measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 41.3% | Only MiMo-V2.6-Pro measured |
| CyberBench (Vals AI) | Not measured | 72.9% | Only MiMo-V2.6-Pro measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 60.9% | MiMo-V2.6-Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | Not measured | Only Gemini 2.5 Pro measured |
| ALE-Bench | Not measured | 1158.1 | Only MiMo-V2.6-Pro measured |
| LMArena Text: coding | 1452 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1459 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | Not measured | 1639 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: HTML | 1235 | 1616 | MiMo-V2.6-Pro |
| LMArena WebDev: from an image | 1285 | 1598 | MiMo-V2.6-Pro |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 46.3 | MiMo-V2.6-Pro |
| Epoch Capabilities Index | 145.1 | Not measured | Only Gemini 2.5 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: agents building web apps | Not measured | 1290 | Only MiMo-V2.6-Pro measured |
| LiveBench research | Not measured | 76.7% | Only MiMo-V2.6-Pro measured |
| LiveBench browser | Not measured | 88.0% | Only MiMo-V2.6-Pro measured |
| LiveBench long agentic | Not measured | 47.5% | Only MiMo-V2.6-Pro measured |
| SREBench (Vals AI) | Not measured | 3.0% | Only MiMo-V2.6-Pro measured |
| Finance Agent (Vals AI) | Not measured | 57.3% | Only MiMo-V2.6-Pro measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.4% | Only MiMo-V2.6-Pro measured |
| Legal Research Bench (Vals AI) | Not measured | 47.1% | Only MiMo-V2.6-Pro measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.8% | Only MiMo-V2.6-Pro measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 62.9% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only MiMo-V2.6-Pro measured |
| τ²-Bench Telecom | 54.1% | Not measured | Only Gemini 2.5 Pro measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| BrowseComp-Plus | 29.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 79.6% | Only MiMo-V2.6-Pro measured |
| MysteryMechanism (Vals AI) | Not measured | 15.3% | Only MiMo-V2.6-Pro measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | Not measured | Only Gemini 2.5 Pro measured |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 49.4% | MiMo-V2.6-Pro |
| GPQA Diamond (Epoch AI run) | 85.3% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI | 41.0% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: hard prompts | 1455 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1452 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1453 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1274 | 1281 | MiMo-V2.6-Pro |
| LMArena Vision: homework | 1281 | 1264 | Gemini 2.5 Pro |
| Kagi LLM Benchmark | 70.3% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tiers 1 to 3 | 24.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 2.5 Pro measured |
| ProofBench | Not measured | 70.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: math | 1450 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1454 | 1511 | MiMo-V2.6-Pro |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | Not measured | Only Gemini 2.5 Pro measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedCode (Vals AI) | 50.6% | 45.0% | Gemini 2.5 Pro |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: science | 1480 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1476 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1480 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1439 | 1468 | MiMo-V2.6-Pro |
| FACTS Benchmark Suite | 61.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1308 | MiMo-V2.6-Pro |
| Design Arena: UI components | 1140 | 1339 | MiMo-V2.6-Pro |
| Design Arena: game dev | 1111 | 1313 | MiMo-V2.6-Pro |
| Design Arena: data viz | 1221 | 1336 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1081 | 1331 | MiMo-V2.6-Pro |
| Design Arena: all code categories | 1152 | 1316 | MiMo-V2.6-Pro |
| LiveBench design | Not measured | 78.5% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index215
| Benchmark | Gemini 2.5 Pro | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 57.8% | Only MiMo-V2.6-Pro measured |
| LiveBench data analysis | Not measured | 72.3% | Only MiMo-V2.6-Pro measured |
| Public Benefits Bench (Vals AI) | Not measured | 68.9% | Only MiMo-V2.6-Pro measured |
| SAGE (Vals AI) | 41.9% | 45.0% | MiMo-V2.6-Pro |
| MedScribe (Vals AI) | 73.5% | 88.3% | MiMo-V2.6-Pro |
| IFBench | 48.7% | Not measured | Only Gemini 2.5 Pro measured |
| Long context reasoning (AA-LCR) | 69.0% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 82.4% | Not measured | Only Gemini 2.5 Pro measured |
| LMCA | 34.8% | Not measured | Only Gemini 2.5 Pro measured |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text | 1458 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1437 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1454 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1263 | 1263 | Gemini 2.5 Pro |
| LMArena Text: English | 1458 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1452 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1507 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: German | 1487 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Japanese | 1461 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Korean | 1434 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: French | 1473 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Spanish | 1474 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Russian | 1461 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: Polish | 1479 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: multi-turn | 1453 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1449 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1454 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1441 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1261 | 1268 | MiMo-V2.6-Pro |
| LMArena Vision: Chinese | 1300 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | 1270 | 1270 | Gemini 2.5 Pro |
| LMArena Vision: humor | 1262 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | 1265 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro 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 | Gemini 2.5 Pro | 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 | Google Gemini 2.5 Pro | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Xiaomi | |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | September 21, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.25 | $0.435 |
| Output $/Mtok | $10.00 | $0.87 |
| Coding index | 19.1 | 65.4 |
| Independent measurements behind it | 3 | 4 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than MiMo-V2.6-Pro for coding?
Pick MiMo-V2.6-Pro for coding: it scores 65.4 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro for work measured by LMArena Vision: homework or MedCode (Vals AI), where it leads.
Which is cheaper, Gemini 2.5 Pro or MiMo-V2.6-Pro?
Gemini 2.5 Pro costs $1.25 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 Gemini 2.5 Pro only.
Which has the bigger context window, Gemini 2.5 Pro or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 2.5 Pro vs MiMo-V2.6-Pro comparison based on?
44 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 3 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.