GLM 4.5 Air vs GLM 4.6V
GLM 4.6V leads GLM 4.5 Air on the Artificial Analysis Intelligence Index, 11.2 to 11.1, and GLM 4.6V costs 1.2x less per output token ($0.90 vs $1.10 per million). Updated October 21, 2026; 31 benchmarks have a result for both.
GLM 4.5 Air or GLM 4.6V: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 4.5 Air for work measured by AA Intelligence Index or Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 31
- GLM 4.5 Air only
- 17
- GLM 4.6V only
- 7
- Like-for-like categories
- 7 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GLM 4.6V
GLM 4.6V leads, 11.2 against 11.1.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 4.5 Air has a Design Arena: websites result, 1146.
Directional only
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
GLM 4.5 Air $0.0008, GLM 4.6V $0.0008 per turn.
List prices
At a glance
- Coding index
- GLM 4.5 Air not benchmarked, GLM 4.6V not benchmarked.
- Widest category
- Agentic work, 14.9 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveCodeBench (Artificial Analysis run): GLM 4.5 Air 68.4% against GLM 4.6V 41.1%, 27.3 points apart on a 0 to 100 scale.
- Output price
- GLM 4.5 Air $1.10 against GLM 4.6V $0.90 per million output tokens, 1.2x apart.
- Context window
- Both take 131K tokens.
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 4.5 Air | Bars | GLM 4.6V | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 4 | 1 | ||
| General | 10 | 3 | ||
| All shared boards | 21 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | GLM 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 68.4% | 41.1% | GLM 4.5 Air |
| Terminal-Bench Hard (Artificial Analysis run) | 20.5% | 14.4% | GLM 4.5 Air |
| GSO-Bench | 2.9% | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: coding | 1397 | 1389 | GLM 4.5 Air |
| LMArena Text: software and IT | 1401 | 1391 | GLM 4.5 Air |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.1 | 11.2 | GLM 4.6V |
| 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 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 46.5% | 31.6% | GLM 4.5 Air |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | GLM 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 73.3% | 71.9% | GLM 4.5 Air |
| Humanity's Last Exam (Artificial Analysis run) | 7.0% | 9.6% | GLM 4.6V |
| LMArena Text: hard prompts | 1379 | 1367 | GLM 4.5 Air |
| LMArena Text: expert | 1370 | 1371 | GLM 4.6V |
| LMArena Text: hard prompts in English | 1388 | 1391 | GLM 4.6V |
| LMArena Vision: diagrams | Not measured | 1182 | Only GLM 4.6V measured |
| LMArena Vision: homework | Not measured | 1155 | Only GLM 4.6V measured |
| Kagi LLM Benchmark | 43.0% | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| AA Math Index | 80.7 | 85.3 | GLM 4.6V |
| AIME 2025 (Artificial Analysis run) | 80.7% | 85.3% | GLM 4.6V |
| LMArena Text: math | 1396 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: mathematical work | 1396 | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | GLM 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 81.5% | 79.9% | GLM 4.5 Air |
| LMArena Text: science | 1407 | 1389 | GLM 4.5 Air |
| LMArena Text: medicine and healthcare | 1402 | 1389 | GLM 4.5 Air |
| LMArena Text: legal and government | 1382 | 1393 | GLM 4.6V |
| LMArena Text: business and finance | 1371 | 1359 | GLM 4.5 Air |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GLM 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| Design Arena: websites | 1146 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: UI components | 1123 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: game dev | 1094 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: data viz | 1186 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: 3D | 1123 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: all code categories | 1137 | Not measured | Only GLM 4.5 Air measured |
| Design Arena: SVG | 1071 | Not measured | Only GLM 4.5 Air measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index103
| Benchmark | GLM 4.5 Air | GLM 4.6V | Leader |
|---|---|---|---|
| IFBench | 37.6% | 30.1% | GLM 4.5 Air |
| Long context reasoning (AA-LCR) | 46.7% | 48.7% | GLM 4.6V |
| LMArena Text | 1384 | 1376 | GLM 4.5 Air |
| LMArena Text: instruction following | 1354 | 1350 | GLM 4.5 Air |
| LMArena Text: creative writing | 1343 | 1347 | GLM 4.6V |
| LMArena Vision | Not measured | 1164 | Only GLM 4.6V measured |
| LMArena Text: English | 1397 | 1395 | GLM 4.5 Air |
| LMArena Text: non-English | 1366 | 1358 | GLM 4.5 Air |
| LMArena Text: Chinese | 1426 | 1425 | GLM 4.5 Air |
| LMArena Text: German | 1377 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Japanese | 1348 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Korean | 1308 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: French | 1400 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Spanish | 1385 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: Russian | 1373 | 1339 | GLM 4.5 Air |
| LMArena Text: Polish | 1368 | Not measured | Only GLM 4.5 Air measured |
| LMArena Text: multi-turn | 1371 | 1359 | GLM 4.5 Air |
| LMArena Text: longer queries | 1366 | 1357 | GLM 4.5 Air |
| LMArena Text: writing and language | 1354 | 1347 | GLM 4.5 Air |
| LMArena Text: entertainment and media | 1339 | 1343 | GLM 4.6V |
| LMArena Vision: English | Not measured | 1179 | Only GLM 4.6V measured |
| LMArena Vision: Chinese | Not measured | 1217 | Only GLM 4.6V measured |
| LMArena Vision: reading text | Not measured | 1171 | Only GLM 4.6V measured |
| LMArena Vision: creative writing | Not measured | 1113 | Only GLM 4.6V measured |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.5 Air | GLM 4.6V | 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
Same cost
Repository review
50K input + 3K output tokens
GLM 4.5 Air costs less
Agent loop
200K input + 10K output tokens
GLM 4.5 Air 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 4.5 Air | Z.ai GLM 4.6V |
|---|---|---|
| Maker | Z.ai | Z.ai |
| Weights | Open weights | Open weights |
| Released | July 25, 2025 | December 8, 2025 |
| Context window | 131K | 131K |
| Input $/Mtok | $0.20 | $0.30 |
| Output $/Mtok | $1.10 | $0.90 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.5 Air better than GLM 4.6V for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5 Air for work measured by AA Intelligence Index or Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GLM 4.5 Air or GLM 4.6V?
GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; GLM 4.6V costs $0.30 and $0.90. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.5 Air or GLM 4.6V?
Neither: both take 131K tokens.
How many benchmarks is the GLM 4.5 Air vs GLM 4.6V comparison based on?
31 benchmarks have a result for both models as of October 21, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and GLM 4.6V's on 0. Where only one model has a result, the page says so instead of naming a winner.