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GLM 4.5 Air vs GLM 4.6

GLM 4.6 leads GLM 4.5 Air on the Artificial Analysis Intelligence Index, 18.5 to 11.1, and GLM 4.5 Air costs 2.0x less per output token ($1.10 vs $2.20 per million). Updated October 22, 2026; 47 benchmarks have a result for both.

Replace GLM 4.5 Air Replace GLM 4.6
GLM 4.5 AirZ.ai
Coding
No data
Overall
No data
Output $/M
$1.10
1
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
46
vs boards won of 47 shared

GLM 4.5 Air or GLM 4.6: which to pick

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding.

Pick GLM 4.5 Air for output tokens 2.0x cheaper ($1.10 vs $2.20 per million) and work measured by Design Arena: data viz, where it leads.

Model AGLM 4.5 AirZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task
Shared results
47
GLM 4.5 Air only
1
GLM 4.6 only
22
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.

At a glance

Coding index
GLM 4.5 Air not benchmarked, GLM 4.6 8.8 from 2 benchmarks.
Widest category
Agentic work, 30.4 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 Air 46.5% against GLM 4.6 76.9%, 30.4 points apart on a 0 to 100 scale.
Output price
GLM 4.5 Air $1.10 against GLM 4.6 $2.20 per million output tokens, 2.0x apart.
Context window
GLM 4.5 Air takes 131K tokens, GLM 4.6 205K.

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.

Boards won, where both have a result
CategoryGLM 4.5 AirBarsGLM 4.6Ties
Coding04
Intelligence01
Agentic work01
Reasoning06
Math04
Knowledge05
Web design16
General019
All shared boards146
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
SWE-bench VerifiedNot measured68.2%Only GLM 4.6 measured
LMArena WebDevNot measured1341Only GLM 4.6 measured
AA Coding IndexNot measured45.8Only GLM 4.6 measured
LiveCodeBench (Vals AI)Not measured81.0%Only GLM 4.6 measured
Vibe Code Bench (Vals AI)Not measured3.1%Only GLM 4.6 measured
LiveCodeBench (Artificial Analysis run)68.4%69.5%GLM 4.6
Terminal-Bench Hard (Artificial Analysis run)20.5%28.8%GLM 4.6
Terminal-BenchNot measured24.5%Only GLM 4.6 measured
GSO-Bench2.9%Not measuredOnly GLM 4.5 Air measured
ALE-BenchNot measured340.8Only GLM 4.6 measured
LMArena Text: coding13971449GLM 4.6
LMArena Text: software and IT14011455GLM 4.6
LMArena WebDev: HTMLNot measured1350Only GLM 4.6 measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
AA Intelligence Index11.118.5GLM 4.6
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
Design Arena: agents building full-stack appsNot measured1029Only GLM 4.6 measured
Design Arena: agents building mobile appsNot measured1096Only GLM 4.6 measured
Design Arena: agents building Android appsNot measured1084Only GLM 4.6 measured
Design Arena: agents building Godot gamesNot measured1180Only GLM 4.6 measured
τ²-Bench Telecom46.5%76.9%GLM 4.6
Berkeley Function Calling Leaderboard (BFCL)Not measured72.4%Only GLM 4.6 measured
BrowseComp-PlusNot measured48.2%Only GLM 4.6 measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
GPQA DiamondNot measured74.5%Only GLM 4.6 measured
GPQA Diamond (Artificial Analysis run)73.3%78.0%GLM 4.6
Humanity's Last Exam (Artificial Analysis run)7.0%14.5%GLM 4.6
LMArena Text: hard prompts13791440GLM 4.6
LMArena Text: expert13701432GLM 4.6
LMArena Text: hard prompts in English13881445GLM 4.6
Kagi LLM Benchmark43.0%45.7%GLM 4.6
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
AIMENot measured92.7%Only GLM 4.6 measured
MGSM (Vals AI)Not measured89.8%Only GLM 4.6 measured
AA Math Index80.786.0GLM 4.6
AIME 2025 (Artificial Analysis run)80.7%86.0%GLM 4.6
LMArena Text: math13961432GLM 4.6
LMArena Text: mathematical work13961447GLM 4.6
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
MMLU ProNot measured82.2%Only GLM 4.6 measured
LegalBench (Vals AI)Not measured79.6%Only GLM 4.6 measured
CorpFin (Vals AI)Not measured56.8%Only GLM 4.6 measured
TaxEval (Vals AI)Not measured66.2%Only GLM 4.6 measured
MedQA (Vals AI)Not measured92.2%Only GLM 4.6 measured
MMLU Pro (Artificial Analysis run)81.5%82.9%GLM 4.6
LMArena Text: science14071456GLM 4.6
LMArena Text: medicine and healthcare14021455GLM 4.6
LMArena Text: legal and government13821448GLM 4.6
LMArena Text: business and finance13711416GLM 4.6
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index16
Web design benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
Design Arena: websites11461174GLM 4.6
Design Arena: UI components11201145GLM 4.6
Design Arena: game dev10941150GLM 4.6
Design Arena: data viz11861161GLM 4.5 Air
Design Arena: 3D11221128GLM 4.6
Design Arena: all code categories11371165GLM 4.6
Design Arena: SVG10711108GLM 4.6
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
IFBench37.6%43.4%GLM 4.6
Long context reasoning (AA-LCR)46.7%54.0%GLM 4.6
LMArena Text13841440GLM 4.6
LMArena Text: instruction following13541410GLM 4.6
LMArena Text: creative writing13431412GLM 4.6
LMArena Text: English13971449GLM 4.6
LMArena Text: non-English13661426GLM 4.6
LMArena Text: Chinese14261499GLM 4.6
LMArena Text: German13771447GLM 4.6
LMArena Text: Japanese13481393GLM 4.6
LMArena Text: Korean13081400GLM 4.6
LMArena Text: French14001459GLM 4.6
LMArena Text: Spanish13851436GLM 4.6
LMArena Text: Russian13731418GLM 4.6
LMArena Text: Polish13681447GLM 4.6
LMArena Text: multi-turn13711427GLM 4.6
LMArena Text: longer queries13661422GLM 4.6
LMArena Text: writing and language13541415GLM 4.6
LMArena Text: entertainment and media13391409GLM 4.6
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.5 Air and GLM 4.6
BenchmarkGLM 4.5 AirGLM 4.6Leader
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 4.5 Air$0.0008Fits in one request
GLM 4.6$0.0017Fits in one request

GLM 4.5 Air costs less

Repository review

50K input + 3K output tokens

GLM 4.5 Air$0.013Fits in one request
GLM 4.6$0.037Fits in one request

GLM 4.5 Air costs less

Agent loop

200K input + 10K output tokens

GLM 4.5 Air$0.051Exceeds the context window
GLM 4.6$0.142Exceeds the context window

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.

Specifications of GLM 4.5 Air and GLM 4.6
SpecificationZ.ai GLM 4.5 AirZ.ai GLM 4.6
MakerZ.aiZ.ai
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025September 30, 2025
Context window131K205K
Input $/Mtok$0.20$0.60
Output $/Mtok$1.10$2.20
Coding indexNot benchmarked8.8
Independent measurements behind it02
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 Air better than GLM 4.6 for coding?

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding. Pick GLM 4.5 Air for output tokens 2.0x cheaper ($1.10 vs $2.20 per million) and work measured by Design Arena: data viz, where it leads.

Which is cheaper, GLM 4.5 Air or GLM 4.6?

GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.5 Air or GLM 4.6?

GLM 4.6, with 205K tokens against 131K.

How many benchmarks is the GLM 4.5 Air vs GLM 4.6 comparison based on?

47 benchmarks have a result for both models as of October 22, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and GLM 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.

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