GLM 5V Turbo vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads GLM 5V Turbo on the Artificial Analysis Intelligence Index, 46.3 to 23.5, and MiMo-V2.6-Pro costs 4.6x less per output token ($0.87 vs $4.00 per million). Updated October 22, 2026; 41 benchmarks have a result for both.
GLM 5V Turbo or MiMo-V2.6-Pro: which to pick
Only MiMo-V2.6-Pro has a coding score, 65.4 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 LMArena Vision: diagrams or LMArena Vision: homework, where it leads.
- Shared results
- 41
- GLM 5V Turbo only
- 24
- MiMo-V2.6-Pro only
- 32
- 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-V2.6-Pro has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 23.5.
Same board, both measured
Web design
Design Arena: websites
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 1307 against 1230.
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 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
GLM 5V Turbo $0.0032, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Coding, 26.6 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: HTML: GLM 5V Turbo 1356 against MiMo-V2.6-Pro 1616, 40.6 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against MiMo-V2.6-Pro $0.87 per million output tokens, 4.6x apart.
- Context window
- GLM 5V Turbo takes 203K 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 | GLM 5V Turbo | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 6 | ||
| General | 3 | 12 | ||
| All shared boards | 5 | 36 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
| Benchmark | GLM 5V Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 81.5% | Only MiMo-V2.6-Pro measured |
| LMArena WebDev | 1402 | 1625 | MiMo-V2.6-Pro |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.3% | Only MiMo-V2.6-Pro measured |
| Vibe Code Bench (Vals AI) | Not measured | 85.2% | Only MiMo-V2.6-Pro measured |
| 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 |
| SciCode | Not measured | 60.9% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | Not measured | Only GLM 5V Turbo measured |
| ALE-Bench | Not measured | 1158.1 | Only MiMo-V2.6-Pro measured |
| LMArena Text: coding | 1466 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1460 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1386 | 1639 | MiMo-V2.6-Pro |
| LMArena WebDev: HTML | 1356 | 1616 | MiMo-V2.6-Pro |
| LMArena WebDev: from an image | 1425 | 1598 | MiMo-V2.6-Pro |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5V Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 46.3 | MiMo-V2.6-Pro |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5V Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1124 | 1290 | MiMo-V2.6-Pro |
| 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 | 1128 | Not measured | Only GLM 5V Turbo 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 | 98.5% | Not measured | Only GLM 5V Turbo measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | GLM 5V Turbo | 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) | 80.9% | Not measured | Only GLM 5V Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 49.4% | MiMo-V2.6-Pro |
| LMArena Text: hard prompts | 1443 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1453 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1456 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1286 | 1281 | GLM 5V Turbo |
| LMArena Vision: homework | 1273 | 1264 | 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 index02
| Benchmark | GLM 5V Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| ProofBench | Not measured | 70.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: math | 1442 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1447 | 1511 | MiMo-V2.6-Pro |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GLM 5V Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: science | 1448 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1433 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1436 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1435 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GLM 5V Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1307 | MiMo-V2.6-Pro |
| Design Arena: UI components | 1210 | 1337 | MiMo-V2.6-Pro |
| Design Arena: game dev | 1218 | 1313 | MiMo-V2.6-Pro |
| Design Arena: data viz | 1202 | 1337 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1208 | 1329 | MiMo-V2.6-Pro |
| Design Arena: all code categories | 1227 | 1316 | MiMo-V2.6-Pro |
| Design Arena: SVG | 1150 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | 1117 | Not measured | Only GLM 5V Turbo measured |
| LiveBench design | Not measured | 78.5% | Only MiMo-V2.6-Pro measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index312
| Benchmark | GLM 5V Turbo | 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) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| MedScribe (Vals AI) | Not measured | 88.3% | Only MiMo-V2.6-Pro measured |
| IFBench | 61.1% | Not measured | Only GLM 5V Turbo measured |
| Long context reasoning (AA-LCR) | 70.3% | 86.3% | MiMo-V2.6-Pro |
| LMArena Text | 1437 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1423 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1417 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1264 | 1263 | GLM 5V Turbo |
| LMArena Text: English | 1454 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1420 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1491 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: German | 1422 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Korean | 1397 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: French | 1443 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Spanish | 1452 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Russian | 1432 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: Polish | 1432 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: multi-turn | 1431 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1438 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1420 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1407 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1274 | 1268 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1329 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | 1270 | 1270 | GLM 5V Turbo |
| LMArena Vision: humor | 1268 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: captioning | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | 1241 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | 1252 | Not measured | Only GLM 5V Turbo measured |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | 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 | Z.ai GLM 5V Turbo | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Z.ai | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | April 1, 2026 | September 21, 2026 |
| Context window | 203K | 1.05M |
| Input $/Mtok | $1.20 | $0.435 |
| Output $/Mtok | $4.00 | $0.87 |
| Coding index | Not benchmarked | 65.4 |
| Independent measurements behind it | 1 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than MiMo-V2.6-Pro for coding?
Only MiMo-V2.6-Pro has a coding score, 65.4 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 LMArena Vision: diagrams or LMArena Vision: homework, where it leads.
Which is cheaper, GLM 5V Turbo or MiMo-V2.6-Pro?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 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, GLM 5V Turbo or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs MiMo-V2.6-Pro comparison based on?
41 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-V2.6-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.