GLM 4.6V vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads GLM 4.6V on the Artificial Analysis Intelligence Index, 46.3 to 11.2, at about the same output price ($0.87 vs $0.90 per million). Updated October 22, 2026; 28 benchmarks have a result for both.
GLM 4.6V 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 4.6V has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 28
- GLM 4.6V only
- 10
- MiMo-V2.6-Pro only
- 45
- Like-for-like categories
- 5 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 11.2.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiMo-V2.6-Pro has a Design Arena: websites result, 1307.
Directional only
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 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.6V
GLM 4.6V $0.0008, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- GLM 4.6V not benchmarked, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Intelligence, 35.1 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): GLM 4.6V 9.6% against MiMo-V2.6-Pro 49.4%, 39.8 points apart on a 0 to 100 scale.
- Output price
- GLM 4.6V $0.90 against MiMo-V2.6-Pro $0.87 per million output tokens, 1.0x apart.
- Context window
- GLM 4.6V takes 131K 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 4.6V | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 6 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 15 | ||
| All shared boards | 0 | 28 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GLM 4.6V | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 81.5% | Only MiMo-V2.6-Pro measured |
| LMArena WebDev | Not measured | 1625 | Only MiMo-V2.6-Pro measured |
| 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 |
| LiveCodeBench (Artificial Analysis run) | 41.1% | Not measured | Only GLM 4.6V measured |
| SciCode | Not measured | 60.9% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 14.4% | Not measured | Only GLM 4.6V measured |
| ALE-Bench | Not measured | 1158.1 | Only MiMo-V2.6-Pro measured |
| LMArena Text: coding | 1389 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1391 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | Not measured | 1639 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: HTML | Not measured | 1616 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: from an image | Not measured | 1598 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.6V | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.2 | 46.3 | MiMo-V2.6-Pro |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | GLM 4.6V | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| 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 | 31.6% | Not measured | Only GLM 4.6V measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GLM 4.6V | 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) | 71.9% | Not measured | Only GLM 4.6V measured |
| Humanity's Last Exam (Artificial Analysis run) | 9.6% | 49.4% | MiMo-V2.6-Pro |
| LMArena Text: hard prompts | 1367 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1371 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1391 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1182 | 1281 | MiMo-V2.6-Pro |
| LMArena Vision: homework | 1155 | 1264 | MiMo-V2.6-Pro |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GLM 4.6V | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Math Index | 85.3 | Not measured | Only GLM 4.6V measured |
| AIME 2025 (Artificial Analysis run) | 85.3% | Not measured | Only GLM 4.6V measured |
| ProofBench | Not measured | 70.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: math | Not measured | 1500 | Only MiMo-V2.6-Pro measured |
| LMArena Text: mathematical work | Not measured | 1511 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GLM 4.6V | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| MMLU Pro (Artificial Analysis run) | 79.9% | Not measured | Only GLM 4.6V measured |
| LMArena Text: science | 1389 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1389 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1393 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1359 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GLM 4.6V | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1307 | Only MiMo-V2.6-Pro measured |
| Design Arena: UI components | Not measured | 1337 | Only MiMo-V2.6-Pro measured |
| Design Arena: game dev | Not measured | 1313 | Only MiMo-V2.6-Pro measured |
| Design Arena: data viz | Not measured | 1337 | Only MiMo-V2.6-Pro measured |
| Design Arena: 3D | Not measured | 1329 | Only MiMo-V2.6-Pro measured |
| Design Arena: all code categories | Not measured | 1316 | Only MiMo-V2.6-Pro measured |
| 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 index015
| Benchmark | GLM 4.6V | 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 | 30.1% | Not measured | Only GLM 4.6V measured |
| Long context reasoning (AA-LCR) | 48.7% | 86.3% | MiMo-V2.6-Pro |
| LMArena Text | 1376 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1350 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1347 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1164 | 1263 | MiMo-V2.6-Pro |
| LMArena Text: English | 1395 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1358 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1425 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: Russian | 1339 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: multi-turn | 1359 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1357 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1347 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1343 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1179 | 1268 | MiMo-V2.6-Pro |
| LMArena Vision: Chinese | 1217 | Not measured | Only GLM 4.6V measured |
| LMArena Vision: reading text | 1171 | 1270 | MiMo-V2.6-Pro |
| LMArena Vision: creative writing | 1113 | Not measured | Only GLM 4.6V measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.6V | 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
GLM 4.6V costs less
Repository review
50K input + 3K output tokens
GLM 4.6V costs less
Agent loop
200K input + 10K output tokens
GLM 4.6V 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 4.6V | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Z.ai | Xiaomi |
| Weights | Open weights | Open weights |
| Released | December 8, 2025 | September 21, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.30 | $0.435 |
| Output $/Mtok | $0.90 | $0.87 |
| Coding index | Not benchmarked | 65.4 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.6V 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 4.6V has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GLM 4.6V or MiMo-V2.6-Pro?
GLM 4.6V costs $0.30 per million input tokens and $0.90 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 4.6V or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 131K.
How many benchmarks is the GLM 4.6V vs MiMo-V2.6-Pro comparison based on?
28 benchmarks have a result for both models as of October 22, 2026. GLM 4.6V's coding index rests on 0 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.