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GLM 5V Turbo vs Qwen3.6 27B

GLM 5V Turbo leads Qwen3.6 27B on the Artificial Analysis Intelligence Index, 23.5 to 21.4, and Qwen3.6 27B costs 1.5x less per output token ($2.70 vs $4.00 per million). Updated October 22, 2026; 7 benchmarks have a result for both.

GLM 5V TurboZ.ai
Coding
No data
Overall
No data
Output $/M
$4.00
2
Qwen3.6 27BQwen
Coding
36.8
Overall
45.3
Output $/M
$2.70
5
vs boards won of 7 shared

GLM 5V Turbo or Qwen3.6 27B: which to pick

Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding.

Pick GLM 5V Turbo for work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.

Shared results
7
GLM 5V Turbo only
58
Qwen3.6 27B only
18
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 5V Turbo not benchmarked, Qwen3.6 27B 36.8 from 2 benchmarks.
Widest category
General, 6.7 points apart on average over 2 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): GLM 5V Turbo 70.3% against Qwen3.6 27B 77.3%, 7.0 points apart on a 0 to 100 scale.
Output price
GLM 5V Turbo $4.00 against Qwen3.6 27B $2.70 per million output tokens, 1.5x apart.
Context window
GLM 5V Turbo takes 203K tokens, Qwen3.6 27B 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 5V TurboBarsQwen3.6 27BTies
Coding01
Intelligence10
Agentic work10
Reasoning02
General02
All shared boards25
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
LMArena WebDev1402Not measuredOnly GLM 5V Turbo measured
AA Coding IndexNot measured53.7Only Qwen3.6 27B measured
SWE-bench Verified (Vals AI)Not measured70.0%Only Qwen3.6 27B measured
Vibe Code Bench (Vals AI)Not measured11.9%Only Qwen3.6 27B measured
SciCodeNot measured42.8%Only Qwen3.6 27B measured
Terminal-Bench Hard (Artificial Analysis run)32.6%34.8%Qwen3.6 27B
LMArena Text: coding1466Not measuredOnly GLM 5V Turbo measured
LMArena Text: software and IT1460Not measuredOnly GLM 5V Turbo measured
LMArena WebDev: React1386Not measuredOnly GLM 5V Turbo measured
LMArena WebDev: HTML1356Not measuredOnly GLM 5V Turbo measured
LMArena WebDev: from an image1425Not measuredOnly GLM 5V Turbo measured
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
AA Intelligence Index23.521.4GLM 5V Turbo
Epoch Capabilities IndexNot measured146.2Only Qwen3.6 27B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
AA Agentic IndexNot measured18.5Only Qwen3.6 27B measured
Design Arena: agents building web apps1124Not measuredOnly GLM 5V Turbo measured
Design Arena: agents building full-stack apps1149Not measuredOnly GLM 5V Turbo measured
Design Arena: agents building mobile apps1134Not measuredOnly GLM 5V Turbo measured
Design Arena: agents building Android apps1267Not measuredOnly GLM 5V Turbo measured
Design Arena: agents building Godot games957Not measuredOnly GLM 5V Turbo measured
Design Arena: agents building games1102Not measuredOnly GLM 5V Turbo measured
Design Arena: HTML slides1060Not measuredOnly GLM 5V Turbo measured
Design Arena: PowerPoint slides1126Not measuredOnly GLM 5V Turbo measured
τ²-Bench Telecom98.5%94.2%GLM 5V Turbo
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
GPQA Diamond (Artificial Analysis run)80.9%84.2%Qwen3.6 27B
Humanity's Last Exam (Artificial Analysis run)17.1%23.1%Qwen3.6 27B
GPQA Diamond (Epoch AI run)Not measured85.9%Only Qwen3.6 27B measured
Mystery game puzzlesNot measured7.0%Only Qwen3.6 27B measured
LMArena Text: hard prompts1443Not measuredOnly GLM 5V Turbo measured
LMArena Text: expert1453Not measuredOnly GLM 5V Turbo measured
LMArena Text: hard prompts in English1456Not measuredOnly GLM 5V Turbo measured
LMArena Vision: diagrams1286Not measuredOnly GLM 5V Turbo measured
LMArena Vision: homework1273Not measuredOnly GLM 5V Turbo measured
Neither model has a result on the other 14 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
OTIS Mock AIMENot measured91.1%Only Qwen3.6 27B measured
FrontierMath, tiers 1 to 3Not measured35.1%Only Qwen3.6 27B measured
LMArena Text: math1442Not measuredOnly GLM 5V Turbo measured
LMArena Text: mathematical work1447Not measuredOnly GLM 5V Turbo measured
Neither model has a result on the other 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Knowledge benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
CaseLaw (Vals AI)Not measured53.2%Only Qwen3.6 27B measured
CorpFin (Vals AI)Not measured62.3%Only Qwen3.6 27B measured
TaxEval (Vals AI)Not measured71.3%Only Qwen3.6 27B measured
MortgageTax (Vals AI)Not measured68.3%Only Qwen3.6 27B measured
LMArena Text: science1448Not measuredOnly GLM 5V Turbo measured
LMArena Text: medicine and healthcare1433Not measuredOnly GLM 5V Turbo measured
LMArena Text: legal and government1436Not measuredOnly GLM 5V Turbo measured
LMArena Text: business and finance1435Not measuredOnly GLM 5V Turbo measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
Design Arena: websites1230Not measuredOnly GLM 5V Turbo measured
Design Arena: UI components1210Not measuredOnly GLM 5V Turbo measured
Design Arena: game dev1218Not measuredOnly GLM 5V Turbo measured
Design Arena: data viz1202Not measuredOnly GLM 5V Turbo measured
Design Arena: 3D1208Not measuredOnly GLM 5V Turbo measured
Design Arena: all code categories1227Not measuredOnly GLM 5V Turbo measured
Design Arena: SVG1150Not measuredOnly GLM 5V Turbo measured
Design Arena: ASCII art1116Not measuredOnly GLM 5V Turbo measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
SAGE (Vals AI)Not measured45.6%Only Qwen3.6 27B measured
IFBench61.1%67.6%Qwen3.6 27B
Long context reasoning (AA-LCR)70.3%77.3%Qwen3.6 27B
DTBenchNot measured78.1%Only Qwen3.6 27B measured
LMCANot measured34.5%Only Qwen3.6 27B measured
LMArena Text1437Not measuredOnly GLM 5V Turbo measured
LMArena Text: instruction following1423Not measuredOnly GLM 5V Turbo measured
LMArena Text: creative writing1417Not measuredOnly GLM 5V Turbo measured
LMArena Vision1264Not measuredOnly GLM 5V Turbo measured
LMArena Text: English1454Not measuredOnly GLM 5V Turbo measured
LMArena Text: non-English1420Not measuredOnly GLM 5V Turbo measured
LMArena Text: Chinese1491Not measuredOnly GLM 5V Turbo measured
LMArena Text: German1422Not measuredOnly GLM 5V Turbo measured
LMArena Text: Korean1397Not measuredOnly GLM 5V Turbo measured
LMArena Text: French1443Not measuredOnly GLM 5V Turbo measured
LMArena Text: Spanish1452Not measuredOnly GLM 5V Turbo measured
LMArena Text: Russian1432Not measuredOnly GLM 5V Turbo measured
LMArena Text: Polish1432Not measuredOnly GLM 5V Turbo measured
LMArena Text: multi-turn1431Not measuredOnly GLM 5V Turbo measured
LMArena Text: longer queries1438Not measuredOnly GLM 5V Turbo measured
LMArena Text: writing and language1420Not measuredOnly GLM 5V Turbo measured
LMArena Text: entertainment and media1407Not measuredOnly GLM 5V Turbo measured
LMArena Vision: English1274Not measuredOnly GLM 5V Turbo measured
LMArena Vision: Chinese1329Not measuredOnly GLM 5V Turbo measured
LMArena Vision: reading text1270Not measuredOnly GLM 5V Turbo measured
LMArena Vision: humor1268Not measuredOnly GLM 5V Turbo measured
LMArena Vision: captioning1264Not measuredOnly GLM 5V Turbo measured
LMArena Vision: recognizing things1241Not measuredOnly GLM 5V Turbo measured
LMArena Vision: creative writing1252Not measuredOnly GLM 5V Turbo measured
LMArena Document1416Not measuredOnly GLM 5V Turbo measured
EQ-Bench 4Not measured1026Only Qwen3.6 27B measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5V Turbo and Qwen3.6 27B
BenchmarkGLM 5V TurboQwen3.6 27BLeader
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 5V Turbo$0.0032Fits in one request
Qwen3.6 27B$0.0018Fits in one request

Qwen3.6 27B costs less

Repository review

50K input + 3K output tokens

GLM 5V Turbo$0.072Fits in one request
Qwen3.6 27B$0.031Fits in one request

Qwen3.6 27B costs less

Agent loop

200K input + 10K output tokens

GLM 5V Turbo$0.280Exceeds the context window
Qwen3.6 27B$0.117Fits in one request

Qwen3.6 27B 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 5V Turbo and Qwen3.6 27B
SpecificationZ.ai GLM 5V TurboQwen3.6 27B
MakerZ.aiQwen
WeightsNo public weights listedOpen weights
ReleasedApril 1, 2026April 27, 2026
Context window203K262K
Input $/Mtok$1.20$0.45
Output $/Mtok$4.00$2.70
Coding indexNot benchmarked36.8
Independent measurements behind it12
Cost per solved taskNot computable$1.30
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5V Turbo better than Qwen3.6 27B for coding?

Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding. Pick GLM 5V Turbo for work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.

Which is cheaper, GLM 5V Turbo or Qwen3.6 27B?

GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.

Which has the bigger context window, GLM 5V Turbo or Qwen3.6 27B?

Qwen3.6 27B, with 262K tokens against 203K.

How many benchmarks is the GLM 5V Turbo vs Qwen3.6 27B comparison based on?

7 benchmarks have a result for both models as of October 22, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.

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