Gemini 2.5 Pro vs MiMo-V2.5
MiMo-V2.5 leads Gemini 2.5 Pro on coding, 50.0 to 19.1 on the Vibe Coding Index, and MiMo-V2.5 costs 29.8x less per output token ($0.336 vs $10.00 per million). Updated October 21, 2026; 62 benchmarks have a result for both.
Gemini 2.5 Pro or MiMo-V2.5: which to pick
Pick MiMo-V2.5 for coding: it scores 50.0 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro.
Pick Gemini 2.5 Pro for work measured by SciCode or LMArena Text: hard prompts, where it leads.
- Shared results
- 62
- Gemini 2.5 Pro only
- 28
- MiMo-V2.5 only
- 18
- 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
MiMo-V2.5
MiMo-V2.5 scores 50.0 against 19.1.
3 benchmarks behind each score
Intelligence
AA Intelligence Index
MiMo-V2.5
MiMo-V2.5 leads, 21.8 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
MiMo-V2.5
MiMo-V2.5 leads, 15.8 against 1.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only MiMo-V2.5 has a GPQA Diamond result, 81.6%.
Directional only
Knowledge
MMLU Pro
No call
Only MiMo-V2.5 has a MMLU Pro result, 82.9%.
Directional only
Web design
Design Arena: websites
MiMo-V2.5
MiMo-V2.5 leads, 1266 against 1167.
Same board, both measured
Long documents
Listed context window
MiMo-V2.5
MiMo-V2.5 takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5
Gemini 2.5 Pro $0.0063, MiMo-V2.5 $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiMo-V2.5
Gemini 2.5 Pro $0.64, MiMo-V2.5 $0.01.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, MiMo-V2.5 50.0 from 3 benchmarks.
- Widest category
- Agentic work, 25.4 points apart on average over 2 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 2.5 Pro 0.4% against MiMo-V2.5 42.2%, 41.8 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against MiMo-V2.5 $0.336 per million output tokens, 29.8x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, MiMo-V2.5 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-V2.5 | Ties |
|---|---|---|---|---|
| Coding | 1 | 8 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 3 | 4 | ||
| Math | 2 | 0 | ||
| Knowledge | 7 | 0 | ||
| Web design | 0 | 6 | ||
| General | 24 | 4 | ||
| All shared boards | 37 | 25 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index18
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | 1438 | MiMo-V2.5 |
| AA Coding Index | 33.3 | 56.8 | MiMo-V2.5 |
| LiveCodeBench (Vals AI) | Not measured | 81.5% | Only MiMo-V2.5 measured |
| SWE-bench Verified (Vals AI) | 54.4% | 71.0% | MiMo-V2.5 |
| Vibe Code Bench (Vals AI) | 0.4% | 42.2% | MiMo-V2.5 |
| Code migration (Vals AI) | Not measured | 14.2% | Only MiMo-V2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 60.7% | Only MiMo-V2.5 measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 43.9% | Gemini 2.5 Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 41.7% | MiMo-V2.5 |
| 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 | 514.0 | Only MiMo-V2.5 measured |
| LMArena Text: coding | 1452 | 1469 | MiMo-V2.5 |
| LMArena Text: software and IT | 1459 | 1463 | MiMo-V2.5 |
| LMArena WebDev: React | Not measured | 1425 | Only MiMo-V2.5 measured |
| LMArena WebDev: HTML | 1235 | 1429 | MiMo-V2.5 |
| LMArena WebDev: from an image | 1285 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 21.8 | MiMo-V2.5 |
| Epoch Capabilities Index | 145.1 | Not measured | Only Gemini 2.5 Pro measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 15.8 | MiMo-V2.5 |
| Finance Agent (Vals AI) | Not measured | 36.7% | Only MiMo-V2.5 measured |
| Tax Agent Bench (Vals AI) | Not measured | 7.8% | Only MiMo-V2.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 9.1% | Only MiMo-V2.5 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 55.1% | Only MiMo-V2.5 measured |
| τ²-Bench Telecom | 54.1% | 90.6% | MiMo-V2.5 |
| 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 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 81.6% | Only MiMo-V2.5 measured |
| MMMU Pro (Vals AI) | Not measured | 80.0% | Only MiMo-V2.5 measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | 84.9% | MiMo-V2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 27.2% | MiMo-V2.5 |
| 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 | 1450 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1459 | MiMo-V2.5 |
| LMArena Text: hard prompts in English | 1453 | 1461 | MiMo-V2.5 |
| LMArena Vision: diagrams | 1274 | 1269 | Gemini 2.5 Pro |
| LMArena Vision: homework | 1281 | 1262 | 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 index20
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | 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 | 16.0% | Only MiMo-V2.5 measured |
| LMArena Text: math | 1450 | 1436 | Gemini 2.5 Pro |
| LMArena Text: mathematical work | 1454 | 1451 | Gemini 2.5 Pro |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.9% | Only MiMo-V2.5 measured |
| LegalBench (Vals AI) | Not measured | 78.9% | Only MiMo-V2.5 measured |
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | 59.9% | Gemini 2.5 Pro |
| TaxEval (Vals AI) | Not measured | 71.8% | Only MiMo-V2.5 measured |
| MortgageTax (Vals AI) | 68.9% | 59.3% | Gemini 2.5 Pro |
| MedCode (Vals AI) | 50.6% | 31.9% | Gemini 2.5 Pro |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: science | 1480 | 1440 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1432 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | 1425 | Gemini 2.5 Pro |
| LMArena Text: business and finance | 1439 | 1432 | Gemini 2.5 Pro |
| FACTS Benchmark Suite | 61.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1266 | MiMo-V2.5 |
| Design Arena: UI components | 1140 | 1258 | MiMo-V2.5 |
| Design Arena: game dev | 1111 | 1249 | MiMo-V2.5 |
| Design Arena: data viz | 1221 | 1249 | MiMo-V2.5 |
| Design Arena: 3D | 1081 | 1216 | MiMo-V2.5 |
| Design Arena: all code categories | 1152 | 1260 | MiMo-V2.5 |
| Design Arena: SVG | Not measured | 1178 | Only MiMo-V2.5 measured |
| Design Arena: ASCII art | Not measured | 1140 | Only MiMo-V2.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index244
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.9% | 43.3% | MiMo-V2.5 |
| MedScribe (Vals AI) | 73.5% | 72.2% | Gemini 2.5 Pro |
| Vals Multimodal Index | Not measured | 52.8% | Only MiMo-V2.5 measured |
| IFBench | 48.7% | 67.1% | MiMo-V2.5 |
| Long context reasoning (AA-LCR) | 69.0% | 73.0% | MiMo-V2.5 |
| 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 | 1428 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1435 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1393 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | 1247 | Gemini 2.5 Pro |
| LMArena Text: English | 1458 | 1447 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1405 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1469 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | 1421 | Gemini 2.5 Pro |
| LMArena Text: Japanese | 1461 | 1306 | Gemini 2.5 Pro |
| LMArena Text: Korean | 1434 | 1361 | Gemini 2.5 Pro |
| LMArena Text: French | 1473 | 1448 | Gemini 2.5 Pro |
| LMArena Text: Spanish | 1474 | 1414 | Gemini 2.5 Pro |
| LMArena Text: Russian | 1461 | 1396 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | 1413 | Gemini 2.5 Pro |
| LMArena Text: multi-turn | 1453 | 1445 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1445 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1409 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1399 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | 1259 | Gemini 2.5 Pro |
| LMArena Vision: Chinese | 1300 | 1326 | MiMo-V2.5 |
| LMArena Vision: reading text | 1270 | 1256 | Gemini 2.5 Pro |
| LMArena Vision: humor | 1262 | 1226 | Gemini 2.5 Pro |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | 1189 | Gemini 2.5 Pro |
| LMArena Vision: creative writing | 1265 | 1230 | Gemini 2.5 Pro |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | MiMo-V2.5 | 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-V2.5 costs less
Repository review
50K input + 3K output tokens
MiMo-V2.5 costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.5 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-V2.5 |
|---|---|---|
| Maker | Xiaomi | |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | April 22, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.25 | $0.168 |
| Output $/Mtok | $10.00 | $0.336 |
| Coding index | 19.1 | 50.0 |
| Independent measurements behind it | 3 | 3 |
| Cost per solved task | $0.64 | $0.01 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than MiMo-V2.5 for coding?
Pick MiMo-V2.5 for coding: it scores 50.0 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro for work measured by SciCode or LMArena Text: hard prompts, where it leads.
Which is cheaper, Gemini 2.5 Pro or MiMo-V2.5?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; MiMo-V2.5 costs $0.168 and $0.336. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and MiMo-V2.5 $0.01.
Which has the bigger context window, Gemini 2.5 Pro or MiMo-V2.5?
MiMo-V2.5, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 2.5 Pro vs MiMo-V2.5 comparison based on?
62 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-V2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.