Ling 3.0 Flash vs MiMo-V2.5-Pro
MiMo-V2.5-Pro leads Ling 3.0 Flash on coding, 31.6 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 7.5x less per output token ($0.1215 vs $0.9152 per million). Updated October 22, 2026; 22 benchmarks have a result for both.
Ling 3.0 Flash or MiMo-V2.5-Pro: which to pick
Pick MiMo-V2.5-Pro for coding: it scores 31.6 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.
Pick Ling 3.0 Flash for output tokens 7.5x cheaper ($0.1215 vs $0.9152 per million) and work measured by LiveCodeBench (Vals AI) or GPQA Diamond, where it leads.
- Shared results
- 22
- Ling 3.0 Flash only
- 2
- MiMo-V2.5-Pro only
- 48
- Like-for-like categories
- 6 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-Pro
MiMo-V2.5-Pro scores 31.6 against 29.6.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 26.0 against 20.1.
Same board, both measured
Agentic work
AA Agentic Index
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 21.3 against 19.3.
Same board, both measured
Reasoning
GPQA Diamond
Ling 3.0 Flash
Ling 3.0 Flash leads, 84.8% against 82.6%.
Same board, both measured
Knowledge
MMLU Pro
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 84.6% against 82.0%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiMo-V2.5-Pro has a Design Arena: websites result, 1266.
Directional only
Long documents
Listed context window
MiMo-V2.5-Pro
MiMo-V2.5-Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, MiMo-V2.5-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiMo-V2.5-Pro
Ling 3.0 Flash $0.05, MiMo-V2.5-Pro $0.03.
Published attempt cost and pass rate
At a glance
- Coding index
- Ling 3.0 Flash 29.6 from 2 benchmarks, MiMo-V2.5-Pro 31.6 from 4 benchmarks.
- Widest category
- Agentic work, 14.8 points apart on average over 4 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Ling 3.0 Flash 2.9% against MiMo-V2.5-Pro 34.1%, 31.2 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash $0.1215 against MiMo-V2.5-Pro $0.9152 per million output tokens, 7.5x apart.
- Context window
- Ling 3.0 Flash takes 262K tokens, MiMo-V2.5-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 | Ling 3.0 Flash | Bars | MiMo-V2.5-Pro | Ties |
|---|---|---|---|---|
| Coding | 1 | 6 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 4 | ||
| Reasoning | 1 | 2 | ||
| Knowledge | 2 | 3 | ||
| General | 0 | 2 | ||
| All shared boards | 4 | 18 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index16
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1480 | Only MiMo-V2.5-Pro measured |
| AA Coding Index | 50.6 | 60.2 | MiMo-V2.5-Pro |
| LiveCodeBench (Vals AI) | 84.0% | 81.3% | Ling 3.0 Flash |
| SWE-bench Verified (Vals AI) | 65.2% | 74.0% | MiMo-V2.5-Pro |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.5% | Only MiMo-V2.5-Pro measured |
| Vibe Code Bench (Vals AI) | 2.9% | 34.1% | MiMo-V2.5-Pro |
| Code migration (Vals AI) | 0.0% | 21.6% | MiMo-V2.5-Pro |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | 57.3% | MiMo-V2.5-Pro |
| SkillsBench (Vals AI) | 27.9% | Not measured | Only Ling 3.0 Flash measured |
| SciCode | 42.0% | 50.6% | MiMo-V2.5-Pro |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 43.2% | Only MiMo-V2.5-Pro measured |
| ALE-Bench | Not measured | 899.8 | Only MiMo-V2.5-Pro measured |
| LMArena Text: coding | Not measured | 1501 | Only MiMo-V2.5-Pro measured |
| LMArena Text: software and IT | Not measured | 1495 | Only MiMo-V2.5-Pro measured |
| LMArena WebDev: React | Not measured | 1469 | Only MiMo-V2.5-Pro measured |
| LMArena WebDev: HTML | Not measured | 1473 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | 26.0 | MiMo-V2.5-Pro |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 19.3 | 21.3 | MiMo-V2.5-Pro |
| Finance Agent (Vals AI) | 30.3% | 41.5% | MiMo-V2.5-Pro |
| Tax Agent Bench (Vals AI) | Not measured | 11.5% | Only MiMo-V2.5-Pro measured |
| Legal Research Bench (Vals AI) | 0.0% | 15.9% | MiMo-V2.5-Pro |
| Excel Modeling Benchmark (Vals AI) | 25.0% | 55.2% | MiMo-V2.5-Pro |
| τ²-Bench Telecom | Not measured | 94.2% | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | 82.6% | Ling 3.0 Flash |
| GPQA Diamond (Artificial Analysis run) | 85.5% | 86.6% | MiMo-V2.5-Pro |
| Humanity's Last Exam (Artificial Analysis run) | 23.7% | 35.7% | MiMo-V2.5-Pro |
| LMArena Text: hard prompts | Not measured | 1486 | Only MiMo-V2.5-Pro measured |
| LMArena Text: expert | Not measured | 1501 | Only MiMo-V2.5-Pro measured |
| LMArena Text: hard prompts in English | Not measured | 1494 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| ProofBench | Not measured | 22.0% | Only MiMo-V2.5-Pro measured |
| LMArena Text: math | Not measured | 1481 | Only MiMo-V2.5-Pro measured |
| LMArena Text: mathematical work | Not measured | 1491 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| MMLU Pro | 82.0% | 84.6% | MiMo-V2.5-Pro |
| LegalBench (Vals AI) | 79.7% | 77.1% | Ling 3.0 Flash |
| CorpFin (Vals AI) | 61.9% | 61.4% | Ling 3.0 Flash |
| TaxEval (Vals AI) | 70.7% | 73.8% | MiMo-V2.5-Pro |
| MedCode (Vals AI) | 32.3% | 32.5% | MiMo-V2.5-Pro |
| LMArena Text: science | Not measured | 1482 | Only MiMo-V2.5-Pro measured |
| LMArena Text: medicine and healthcare | Not measured | 1473 | Only MiMo-V2.5-Pro measured |
| LMArena Text: legal and government | Not measured | 1474 | Only MiMo-V2.5-Pro measured |
| LMArena Text: business and finance | Not measured | 1466 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1266 | Only MiMo-V2.5-Pro measured |
| Design Arena: UI components | Not measured | 1246 | Only MiMo-V2.5-Pro measured |
| Design Arena: game dev | Not measured | 1261 | Only MiMo-V2.5-Pro measured |
| Design Arena: data viz | Not measured | 1257 | Only MiMo-V2.5-Pro measured |
| Design Arena: 3D | Not measured | 1243 | Only MiMo-V2.5-Pro measured |
| Design Arena: all code categories | Not measured | 1265 | Only MiMo-V2.5-Pro measured |
| Design Arena: SVG | Not measured | 1181 | Only MiMo-V2.5-Pro measured |
| Design Arena: ASCII art | Not measured | 1156 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 50.7% | Not measured | Only Ling 3.0 Flash measured |
| MedScribe (Vals AI) | 80.9% | 83.7% | MiMo-V2.5-Pro |
| IFBench | Not measured | 79.9% | Only MiMo-V2.5-Pro measured |
| Long context reasoning (AA-LCR) | 73.0% | 79.7% | MiMo-V2.5-Pro |
| DTBench | Not measured | 84.5% | Only MiMo-V2.5-Pro measured |
| LMCA | Not measured | 29.5% | Only MiMo-V2.5-Pro measured |
| LMArena Text | Not measured | 1464 | Only MiMo-V2.5-Pro measured |
| LMArena Text: instruction following | Not measured | 1475 | Only MiMo-V2.5-Pro measured |
| LMArena Text: creative writing | Not measured | 1438 | Only MiMo-V2.5-Pro measured |
| LMArena Text: English | Not measured | 1477 | Only MiMo-V2.5-Pro measured |
| LMArena Text: non-English | Not measured | 1448 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Chinese | Not measured | 1507 | Only MiMo-V2.5-Pro measured |
| LMArena Text: German | Not measured | 1459 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Japanese | Not measured | 1410 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Korean | Not measured | 1435 | Only MiMo-V2.5-Pro measured |
| LMArena Text: French | Not measured | 1487 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Spanish | Not measured | 1469 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Russian | Not measured | 1449 | Only MiMo-V2.5-Pro measured |
| LMArena Text: Polish | Not measured | 1464 | Only MiMo-V2.5-Pro measured |
| LMArena Text: multi-turn | Not measured | 1476 | Only MiMo-V2.5-Pro measured |
| LMArena Text: longer queries | Not measured | 1481 | Only MiMo-V2.5-Pro measured |
| LMArena Text: writing and language | Not measured | 1451 | Only MiMo-V2.5-Pro measured |
| LMArena Text: entertainment and media | Not measured | 1438 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash | MiMo-V2.5-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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 | inclusionAI Ling 3.0 Flash | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Maker | inclusionAI | Xiaomi |
| Weights | Open weights | Open weights |
| Released | July 23, 2026 | April 22, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.0405 | $0.4575 |
| Output $/Mtok | $0.1215 | $0.9152 |
| Coding index | 29.6 | 31.6 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | $0.05 | $0.03 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than MiMo-V2.5-Pro for coding?
Pick MiMo-V2.5-Pro for coding: it scores 31.6 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 7.5x cheaper ($0.1215 vs $0.9152 per million) and work measured by LiveCodeBench (Vals AI) or GPQA Diamond, where it leads.
Which is cheaper, Ling 3.0 Flash or MiMo-V2.5-Pro?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; MiMo-V2.5-Pro costs $0.4575 and $0.9152. Per solved SWE-bench Verified task, Ling 3.0 Flash costs $0.05 and MiMo-V2.5-Pro $0.03.
Which has the bigger context window, Ling 3.0 Flash or MiMo-V2.5-Pro?
MiMo-V2.5-Pro, with 1.05M tokens against 262K.
How many benchmarks is the Ling 3.0 Flash vs MiMo-V2.5-Pro comparison based on?
22 benchmarks have a result for both models as of October 22, 2026. Ling 3.0 Flash's coding index rests on 2 independent benchmarks and MiMo-V2.5-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.