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GLM 4.5 Air vs Qwen3.5-9B

Qwen3.5-9B leads GLM 4.5 Air on the Artificial Analysis Intelligence Index, 13.3 to 11.1, and Qwen3.5-9B costs 7.3x less per output token ($0.15 vs $1.10 per million). Updated October 22, 2026; 7 benchmarks have a result for both.

GLM 4.5 AirZ.ai
Coding
No data
Overall
No data
Output $/M
$1.10
0
Qwen3.5-9BQwen
Coding
No data
Overall
No data
Output $/M
$0.15
7
vs boards won of 7 shared

GLM 4.5 Air or Qwen3.5-9B: 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 Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Shared results
7
GLM 4.5 Air only
41
Qwen3.5-9B only
8
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.

At a glance

Coding index
GLM 4.5 Air not benchmarked, Qwen3.5-9B not benchmarked.
Widest category
Agentic work, 40.4 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 Air 46.5% against Qwen3.5-9B 86.8%, 40.4 points apart on a 0 to 100 scale.
Output price
GLM 4.5 Air $1.10 against Qwen3.5-9B $0.15 per million output tokens, 7.3x apart.
Context window
GLM 4.5 Air takes 131K tokens, Qwen3.5-9B 262K.

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 AirBarsQwen3.5-9BTies
Coding01
Intelligence01
Agentic work01
Reasoning02
General02
All shared boards07
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
AA Coding IndexNot measured23.5Only Qwen3.5-9B measured
LiveCodeBench (Artificial Analysis run)68.4%Not measuredOnly GLM 4.5 Air measured
SciCodeNot measured29.5%Only Qwen3.5-9B measured
Terminal-Bench Hard (Artificial Analysis run)20.5%24.2%Qwen3.5-9B
Terminal-BenchNot measured9.2%Only Qwen3.5-9B measured
GSO-Bench2.9%Not measuredOnly GLM 4.5 Air measured
LMArena Text: coding1397Not measuredOnly GLM 4.5 Air measured
LMArena Text: software and IT1401Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
AA Intelligence Index11.113.3Qwen3.5-9B
Epoch Capabilities IndexNot measured139.3Only Qwen3.5-9B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
τ²-Bench Telecom46.5%86.8%Qwen3.5-9B
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
GPQA Diamond (Artificial Analysis run)73.3%80.6%Qwen3.5-9B
Humanity's Last Exam (Artificial Analysis run)7.0%14.9%Qwen3.5-9B
GPQA Diamond (Epoch AI run)Not measured79.0%Only Qwen3.5-9B measured
LMArena Text: hard prompts1379Not measuredOnly GLM 4.5 Air measured
LMArena Text: expert1370Not measuredOnly GLM 4.5 Air measured
LMArena Text: hard prompts in English1388Not measuredOnly GLM 4.5 Air measured
Kagi LLM Benchmark43.0%Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
AA Math Index80.7Not measuredOnly GLM 4.5 Air measured
AIME 2025 (Artificial Analysis run)80.7%Not measuredOnly GLM 4.5 Air measured
OTIS Mock AIMENot measured61.7%Only Qwen3.5-9B measured
LMArena Text: math1396Not measuredOnly GLM 4.5 Air measured
LMArena Text: mathematical work1396Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
MMLU Pro (Artificial Analysis run)81.5%Not measuredOnly GLM 4.5 Air measured
LMArena Text: science1407Not measuredOnly GLM 4.5 Air measured
LMArena Text: medicine and healthcare1402Not measuredOnly GLM 4.5 Air measured
LMArena Text: legal and government1382Not measuredOnly GLM 4.5 Air measured
LMArena Text: business and finance1371Not measuredOnly GLM 4.5 Air measured
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
Web design benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
Design Arena: websites1146Not measuredOnly GLM 4.5 Air measured
Design Arena: UI components1120Not measuredOnly GLM 4.5 Air measured
Design Arena: game dev1094Not measuredOnly GLM 4.5 Air measured
Design Arena: data viz1186Not measuredOnly GLM 4.5 Air measured
Design Arena: 3D1122Not measuredOnly GLM 4.5 Air measured
Design Arena: all code categories1137Not measuredOnly GLM 4.5 Air measured
Design Arena: SVG1071Not measuredOnly 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 index02
General benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
IFBench37.6%66.7%Qwen3.5-9B
Long context reasoning (AA-LCR)46.7%70.0%Qwen3.5-9B
DTBenchNot measured71.2%Only Qwen3.5-9B measured
LMCANot measured24.5%Only Qwen3.5-9B measured
LMArena Text1384Not measuredOnly GLM 4.5 Air measured
LMArena Text: instruction following1354Not measuredOnly GLM 4.5 Air measured
LMArena Text: creative writing1343Not measuredOnly GLM 4.5 Air measured
LMArena Text: English1397Not measuredOnly GLM 4.5 Air measured
LMArena Text: non-English1366Not measuredOnly GLM 4.5 Air measured
LMArena Text: Chinese1426Not measuredOnly GLM 4.5 Air measured
LMArena Text: German1377Not measuredOnly GLM 4.5 Air measured
LMArena Text: Japanese1348Not measuredOnly GLM 4.5 Air measured
LMArena Text: Korean1308Not measuredOnly GLM 4.5 Air measured
LMArena Text: French1400Not measuredOnly GLM 4.5 Air measured
LMArena Text: Spanish1385Not measuredOnly GLM 4.5 Air measured
LMArena Text: Russian1373Not measuredOnly GLM 4.5 Air measured
LMArena Text: Polish1368Not measuredOnly GLM 4.5 Air measured
LMArena Text: multi-turn1371Not measuredOnly GLM 4.5 Air measured
LMArena Text: longer queries1366Not measuredOnly GLM 4.5 Air measured
LMArena Text: writing and language1354Not measuredOnly GLM 4.5 Air measured
LMArena Text: entertainment and media1339Not measuredOnly GLM 4.5 Air 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
Image generation benchmarks for GLM 4.5 Air and Qwen3.5-9B
BenchmarkGLM 4.5 AirQwen3.5-9BLeader
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
Qwen3.5-9B$0.0002Fits in one request

Qwen3.5-9B costs less

Repository review

50K input + 3K output tokens

GLM 4.5 Air$0.013Fits in one request
Qwen3.5-9B$0.0054Fits in one request

Qwen3.5-9B costs less

Agent loop

200K input + 10K output tokens

GLM 4.5 Air$0.051Exceeds the context window
Qwen3.5-9B$0.021Fits in one request

Qwen3.5-9B 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 Qwen3.5-9B
SpecificationZ.ai GLM 4.5 AirQwen3.5-9B
MakerZ.aiQwen
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025March 10, 2026
Context window131K262K
Input $/Mtok$0.20$0.10
Output $/Mtok$1.10$0.15
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 Air better than Qwen3.5-9B 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 Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, GLM 4.5 Air or Qwen3.5-9B?

GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; Qwen3.5-9B costs $0.10 and $0.15. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.5 Air or Qwen3.5-9B?

Qwen3.5-9B, with 262K tokens against 131K.

How many benchmarks is the GLM 4.5 Air vs Qwen3.5-9B comparison based on?

7 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 Qwen3.5-9B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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