GLM 5V Turbo vs MiMo-V2.5
GLM 5V Turbo leads MiMo-V2.5 on the Artificial Analysis Intelligence Index, 23.5 to 21.8, and MiMo-V2.5 costs 11.9x less per output token ($0.336 vs $4.00 per million). Updated October 22, 2026; 54 benchmarks have a result for both.
GLM 5V Turbo or MiMo-V2.5: which to pick
Only MiMo-V2.5 has a coding score, 50.0 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding.
Pick GLM 5V Turbo for work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.
- Shared results
- 54
- GLM 5V Turbo only
- 11
- MiMo-V2.5 only
- 26
- 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
No call
Only MiMo-V2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GLM 5V Turbo
GLM 5V Turbo leads, 23.5 against 21.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiMo-V2.5 has a AA Agentic Index result, 15.8.
Directional only
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, 1265 against 1230.
Same board, both measured
Long documents
Listed context window
MiMo-V2.5
MiMo-V2.5 takes 1.05M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5
GLM 5V Turbo $0.0032, MiMo-V2.5 $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiMo-V2.5 has the number, $0.01.
Directional only
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, MiMo-V2.5 50.0 from 3 benchmarks.
- Widest category
- Agentic work, 7.9 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena WebDev: HTML: GLM 5V Turbo 1356 against MiMo-V2.5 1429, 12.2 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against MiMo-V2.5 $0.336 per million output tokens, 11.9x apart.
- Context window
- GLM 5V Turbo takes 203K 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 | GLM 5V Turbo | Bars | MiMo-V2.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 5 | ||
| Math | 1 | 1 | ||
| Knowledge | 4 | 0 | ||
| Web design | 0 | 8 | ||
| General | 19 | 6 | ||
| All shared boards | 28 | 26 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
| Benchmark | GLM 5V Turbo | MiMo-V2.5 | Leader |
|---|---|---|---|
| LMArena WebDev | 1402 | 1438 | MiMo-V2.5 |
| AA Coding Index | Not measured | 56.8 | Only MiMo-V2.5 measured |
| LiveCodeBench (Vals AI) | Not measured | 81.5% | Only MiMo-V2.5 measured |
| SWE-bench Verified (Vals AI) | Not measured | 71.0% | Only MiMo-V2.5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 42.2% | Only MiMo-V2.5 measured |
| 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 |
| SciCode | Not measured | 43.9% | Only MiMo-V2.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | 41.7% | MiMo-V2.5 |
| ALE-Bench | Not measured | 514.0 | Only MiMo-V2.5 measured |
| LMArena Text: coding | 1466 | 1469 | MiMo-V2.5 |
| LMArena Text: software and IT | 1460 | 1463 | MiMo-V2.5 |
| LMArena WebDev: React | 1386 | 1425 | MiMo-V2.5 |
| LMArena WebDev: HTML | 1356 | 1429 | MiMo-V2.5 |
| LMArena WebDev: from an image | 1425 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 21.8 | GLM 5V Turbo |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | MiMo-V2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 15.8 | Only MiMo-V2.5 measured |
| Design Arena: agents building web apps | 1124 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | 1149 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | 1134 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | 1267 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | 957 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building games | 1102 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | 1070 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | 1127 | Not measured | Only GLM 5V Turbo measured |
| 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 | 98.5% | 90.6% | GLM 5V Turbo |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | GLM 5V Turbo | 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) | 80.9% | 84.9% | MiMo-V2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 27.2% | MiMo-V2.5 |
| LMArena Text: hard prompts | 1443 | 1450 | MiMo-V2.5 |
| LMArena Text: expert | 1453 | 1459 | MiMo-V2.5 |
| LMArena Text: hard prompts in English | 1456 | 1461 | MiMo-V2.5 |
| LMArena Vision: diagrams | 1286 | 1269 | GLM 5V Turbo |
| LMArena Vision: homework | 1273 | 1262 | GLM 5V Turbo |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GLM 5V Turbo | MiMo-V2.5 | Leader |
|---|---|---|---|
| ProofBench | Not measured | 16.0% | Only MiMo-V2.5 measured |
| LMArena Text: math | 1442 | 1436 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1447 | 1451 | MiMo-V2.5 |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GLM 5V Turbo | 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 |
| CorpFin (Vals AI) | Not measured | 59.9% | Only MiMo-V2.5 measured |
| TaxEval (Vals AI) | Not measured | 71.8% | Only MiMo-V2.5 measured |
| MortgageTax (Vals AI) | Not measured | 59.3% | Only MiMo-V2.5 measured |
| MedCode (Vals AI) | Not measured | 31.9% | Only MiMo-V2.5 measured |
| LMArena Text: science | 1448 | 1440 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1433 | 1432 | GLM 5V Turbo |
| LMArena Text: legal and government | 1436 | 1425 | GLM 5V Turbo |
| LMArena Text: business and finance | 1435 | 1432 | GLM 5V Turbo |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | GLM 5V Turbo | MiMo-V2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1265 | MiMo-V2.5 |
| Design Arena: UI components | 1210 | 1255 | MiMo-V2.5 |
| Design Arena: game dev | 1218 | 1249 | MiMo-V2.5 |
| Design Arena: data viz | 1202 | 1250 | MiMo-V2.5 |
| Design Arena: 3D | 1208 | 1215 | MiMo-V2.5 |
| Design Arena: all code categories | 1228 | 1260 | MiMo-V2.5 |
| Design Arena: SVG | 1151 | 1179 | MiMo-V2.5 |
| Design Arena: ASCII art | 1117 | 1140 | MiMo-V2.5 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index196
| Benchmark | GLM 5V Turbo | MiMo-V2.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 43.3% | Only MiMo-V2.5 measured |
| MedScribe (Vals AI) | Not measured | 72.2% | Only MiMo-V2.5 measured |
| Vals Multimodal Index | Not measured | 52.8% | Only MiMo-V2.5 measured |
| IFBench | 61.1% | 67.1% | MiMo-V2.5 |
| Long context reasoning (AA-LCR) | 70.3% | 73.0% | MiMo-V2.5 |
| LMArena Text | 1437 | 1428 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1435 | MiMo-V2.5 |
| LMArena Text: creative writing | 1417 | 1393 | GLM 5V Turbo |
| LMArena Vision | 1264 | 1247 | GLM 5V Turbo |
| LMArena Text: English | 1454 | 1447 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1405 | GLM 5V Turbo |
| LMArena Text: Chinese | 1491 | 1469 | GLM 5V Turbo |
| LMArena Text: German | 1422 | 1421 | GLM 5V Turbo |
| LMArena Text: Japanese | Not measured | 1306 | Only MiMo-V2.5 measured |
| LMArena Text: Korean | 1397 | 1361 | GLM 5V Turbo |
| LMArena Text: French | 1443 | 1448 | MiMo-V2.5 |
| LMArena Text: Spanish | 1452 | 1414 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1396 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | 1413 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1431 | 1445 | MiMo-V2.5 |
| LMArena Text: longer queries | 1438 | 1445 | MiMo-V2.5 |
| LMArena Text: writing and language | 1420 | 1409 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1399 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | 1259 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1329 | 1326 | GLM 5V Turbo |
| LMArena Vision: reading text | 1270 | 1256 | GLM 5V Turbo |
| LMArena Vision: humor | 1268 | 1226 | GLM 5V Turbo |
| LMArena Vision: captioning | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | 1241 | 1189 | GLM 5V Turbo |
| LMArena Vision: creative writing | 1252 | 1230 | GLM 5V Turbo |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | 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 | Z.ai GLM 5V Turbo | Xiaomi MiMo-V2.5 |
|---|---|---|
| Maker | Z.ai | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | April 1, 2026 | April 22, 2026 |
| Context window | 203K | 1.05M |
| Input $/Mtok | $1.20 | $0.168 |
| Output $/Mtok | $4.00 | $0.336 |
| Coding index | Not benchmarked | 50.0 |
| Independent measurements behind it | 1 | 3 |
| Cost per solved task | Not computable | $0.01 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than MiMo-V2.5 for coding?
Only MiMo-V2.5 has a coding score, 50.0 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding. Pick GLM 5V Turbo for work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.
Which is cheaper, GLM 5V Turbo or MiMo-V2.5?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; MiMo-V2.5 costs $0.168 and $0.336. Cost per solved task is known for MiMo-V2.5 only.
Which has the bigger context window, GLM 5V Turbo or MiMo-V2.5?
MiMo-V2.5, with 1.05M tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs MiMo-V2.5 comparison based on?
54 benchmarks have a result for both models as of October 22, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and MiMo-V2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.