GLM 4.5V vs MiMo-V2.6-Flash
MiMo-V2.6-Flash leads GLM 4.5V on the Artificial Analysis Intelligence Index, 37.9 to 7.6, and MiMo-V2.6-Flash costs 6.4x less per output token ($0.28 vs $1.80 per million). Updated October 21, 2026; 32 benchmarks have a result for both.
GLM 4.5V or MiMo-V2.6-Flash: which to pick
Only MiMo-V2.6-Flash has a coding score, 54.7 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 32
- GLM 4.5V only
- 9
- MiMo-V2.6-Flash only
- 34
- 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
No call
Only MiMo-V2.6-Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiMo-V2.6-Flash
MiMo-V2.6-Flash leads, 37.9 against 7.6.
Same board, both measured
General
Vals Index
No call
Only MiMo-V2.6-Flash has a Vals Index result, 54.8%.
Directional only
Long documents
Listed context window
MiMo-V2.6-Flash
MiMo-V2.6-Flash takes 1.05M tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Flash
GLM 4.5V $0.0015, MiMo-V2.6-Flash $0.0003 per turn.
List prices
At a glance
- Coding index
- GLM 4.5V not benchmarked, MiMo-V2.6-Flash 54.7 from 3 benchmarks.
- Widest category
- Intelligence, 30.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): GLM 4.5V 0.0% against MiMo-V2.6-Flash 74.3%, 74.3 points apart on a 0 to 100 scale.
- Output price
- GLM 4.5V $1.80 against MiMo-V2.6-Flash $0.28 per million output tokens, 6.4x apart.
- Context window
- GLM 4.5V takes 66K tokens, MiMo-V2.6-Flash 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 4.5V | Bars | MiMo-V2.6-Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 32 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1634 | Only MiMo-V2.6-Flash measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 24.2% | Only MiMo-V2.6-Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 79.0% | Only MiMo-V2.6-Flash measured |
| Code migration (Vals AI) | Not measured | 40.9% | Only MiMo-V2.6-Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only MiMo-V2.6-Flash measured |
| IOI (Vals AI) | Not measured | 47.7% | Only MiMo-V2.6-Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 76.4% | Only MiMo-V2.6-Flash measured |
| CyberBench (Vals AI) | Not measured | 75.4% | Only MiMo-V2.6-Flash measured |
| LiveCodeBench (Artificial Analysis run) | 60.4% | Not measured | Only GLM 4.5V measured |
| SciCode | Not measured | 51.3% | Only MiMo-V2.6-Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | Not measured | Only GLM 4.5V measured |
| ALE-Bench | Not measured | 1244.2 | Only MiMo-V2.6-Flash measured |
| LMArena Text: coding | 1347 | 1499 | MiMo-V2.6-Flash |
| LMArena Text: software and IT | 1353 | 1497 | MiMo-V2.6-Flash |
| LMArena WebDev: React | Not measured | 1648 | Only MiMo-V2.6-Flash measured |
| LMArena WebDev: HTML | Not measured | 1641 | Only MiMo-V2.6-Flash measured |
| LMArena WebDev: from an image | Not measured | 1596 | Only MiMo-V2.6-Flash measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.6 | 37.9 | MiMo-V2.6-Flash |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| SREBench (Vals AI) | Not measured | 4.2% | Only MiMo-V2.6-Flash measured |
| Finance Agent (Vals AI) | Not measured | 56.3% | Only MiMo-V2.6-Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 28.5% | Only MiMo-V2.6-Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 38.0% | Only MiMo-V2.6-Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.3% | Only MiMo-V2.6-Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 65.5% | Only MiMo-V2.6-Flash measured |
| BioMysteryBench (Vals AI) | Not measured | 69.3% | Only MiMo-V2.6-Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 4.3% | Only MiMo-V2.6-Flash measured |
| Vals Science Index | Not measured | 31.7% | Only MiMo-V2.6-Flash measured |
| τ²-Bench Telecom | 22.5% | Not measured | Only GLM 4.5V measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | Not measured | 21.6% | Only MiMo-V2.6-Flash measured |
| GPQA Diamond (Artificial Analysis run) | 68.4% | Not measured | Only GLM 4.5V measured |
| Humanity's Last Exam (Artificial Analysis run) | 6.3% | 35.1% | MiMo-V2.6-Flash |
| LMArena Text: hard prompts | 1335 | 1475 | MiMo-V2.6-Flash |
| LMArena Text: expert | 1353 | 1496 | MiMo-V2.6-Flash |
| LMArena Text: hard prompts in English | 1357 | 1493 | MiMo-V2.6-Flash |
| LMArena Vision: diagrams | 1151 | 1276 | MiMo-V2.6-Flash |
| LMArena Vision: homework | 1163 | 1283 | MiMo-V2.6-Flash |
| Kagi LLM Benchmark | 59.8% | Not measured | Only GLM 4.5V measured |
| 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 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| AA Math Index | 73.0 | Not measured | Only GLM 4.5V measured |
| AIME 2025 (Artificial Analysis run) | 73.0% | Not measured | Only GLM 4.5V measured |
| ProofBench | Not measured | 63.0% | Only MiMo-V2.6-Flash measured |
| LMArena Text: math | 1354 | 1476 | MiMo-V2.6-Flash |
| LMArena Text: mathematical work | 1336 | 1478 | MiMo-V2.6-Flash |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 41.1% | Only MiMo-V2.6-Flash measured |
| MMLU Pro (Artificial Analysis run) | 78.8% | Not measured | Only GLM 4.5V measured |
| LMArena Text: science | 1330 | 1462 | MiMo-V2.6-Flash |
| LMArena Text: medicine and healthcare | 1349 | 1439 | MiMo-V2.6-Flash |
| LMArena Text: legal and government | 1338 | 1441 | MiMo-V2.6-Flash |
| LMArena Text: business and finance | 1309 | 1454 | MiMo-V2.6-Flash |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 54.8% | Only MiMo-V2.6-Flash measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.6% | Only MiMo-V2.6-Flash measured |
| SAGE (Vals AI) | Not measured | 43.5% | Only MiMo-V2.6-Flash measured |
| MedScribe (Vals AI) | Not measured | 85.3% | Only MiMo-V2.6-Flash measured |
| IFBench | 34.2% | Not measured | Only GLM 4.5V measured |
| Long context reasoning (AA-LCR) | 0.0% | 74.3% | MiMo-V2.6-Flash |
| LMArena Text | 1333 | 1453 | MiMo-V2.6-Flash |
| LMArena Text: instruction following | 1311 | 1452 | MiMo-V2.6-Flash |
| LMArena Text: creative writing | 1294 | 1403 | MiMo-V2.6-Flash |
| LMArena Vision | 1154 | 1256 | MiMo-V2.6-Flash |
| LMArena Text: English | 1362 | 1476 | MiMo-V2.6-Flash |
| LMArena Text: non-English | 1303 | 1431 | MiMo-V2.6-Flash |
| LMArena Text: Chinese | 1337 | 1509 | MiMo-V2.6-Flash |
| LMArena Text: German | Not measured | 1458 | Only MiMo-V2.6-Flash measured |
| LMArena Text: Japanese | Not measured | 1359 | Only MiMo-V2.6-Flash measured |
| LMArena Text: Korean | Not measured | 1425 | Only MiMo-V2.6-Flash measured |
| LMArena Text: French | Not measured | 1480 | Only MiMo-V2.6-Flash measured |
| LMArena Text: Spanish | 1336 | 1453 | MiMo-V2.6-Flash |
| LMArena Text: Russian | 1298 | 1409 | MiMo-V2.6-Flash |
| LMArena Text: Polish | 1302 | 1455 | MiMo-V2.6-Flash |
| LMArena Text: multi-turn | 1333 | 1447 | MiMo-V2.6-Flash |
| LMArena Text: longer queries | 1305 | 1459 | MiMo-V2.6-Flash |
| LMArena Text: writing and language | 1302 | 1424 | MiMo-V2.6-Flash |
| LMArena Text: entertainment and media | 1303 | 1415 | MiMo-V2.6-Flash |
| LMArena Vision: English | 1183 | 1269 | MiMo-V2.6-Flash |
| LMArena Vision: reading text | 1151 | 1270 | MiMo-V2.6-Flash |
| LMArena Vision: creative writing | Not measured | 1231 | Only MiMo-V2.6-Flash measured |
| Neither model has a result on the other 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.5V | MiMo-V2.6-Flash | 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-Flash costs less
Repository review
50K input + 3K output tokens
MiMo-V2.6-Flash costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.6-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 | Z.ai GLM 4.5V | Xiaomi MiMo-V2.6-Flash |
|---|---|---|
| Maker | Z.ai | Xiaomi |
| Weights | Open weights | Open weights |
| Released | August 11, 2025 | September 21, 2026 |
| Context window | 66K | 1.05M |
| Input $/Mtok | $0.60 | $0.14 |
| Output $/Mtok | $1.80 | $0.28 |
| Coding index | Not benchmarked | 54.7 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.5V better than MiMo-V2.6-Flash for coding?
Only MiMo-V2.6-Flash has a coding score, 54.7 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GLM 4.5V or MiMo-V2.6-Flash?
GLM 4.5V costs $0.60 per million input tokens and $1.80 per million output tokens; MiMo-V2.6-Flash costs $0.14 and $0.28. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.5V or MiMo-V2.6-Flash?
MiMo-V2.6-Flash, with 1.05M tokens against 66K.
How many benchmarks is the GLM 4.5V vs MiMo-V2.6-Flash comparison based on?
32 benchmarks have a result for both models as of October 21, 2026. GLM 4.5V's coding index rests on 0 independent benchmarks and MiMo-V2.6-Flash's on 3. Where only one model has a result, the page says so instead of naming a winner.