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GLM 5 vs Qwen3 235B A22B Thinking 2507

GLM 5 leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 27.9 to 12.7, at about the same output price ($3.20 vs $3.50 per million). Updated October 22, 2026; 38 benchmarks have a result for both.

GLM 5Z.ai
Coding
41.7
Overall
54.3
Output $/M
$3.20
35
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
3
vs boards won of 38 shared

GLM 5 or Qwen3 235B A22B Thinking 2507: which to pick

Only GLM 5 has a coding score, 41.7 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding.

Pick Qwen3 235B A22B Thinking 2507 for work measured by LMArena Text: expert or OTIS Mock AIME, where it leads.

Shared results
38
GLM 5 only
38
Qwen3 235B A22B Thinking 2507 only
8
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 5 41.7 from 3 benchmarks, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
Web design, 30.9 points apart on average over 6 shared benchmarks.
Widest single gap
Design Arena: UI components: GLM 5 1227 against Qwen3 235B A22B Thinking 2507 942, 35.6 points apart on a 0 to 100 scale.
Output price
GLM 5 $3.20 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 1.1x apart.
Context window
GLM 5 takes 205K tokens, Qwen3 235B A22B Thinking 2507 128K.

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 5BarsQwen3 235B A22B Thinking 2507Ties
Coding30
Intelligence10
Agentic work10
Reasoning31
Math21
Knowledge31
Web design60
General160
All shared boards353
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
SWE-bench Verified72.8%Not measuredOnly GLM 5 measured
SWE-bench Multilingual69.7%Not measuredOnly GLM 5 measured
LMArena WebDev1435Not measuredOnly GLM 5 measured
AA Coding IndexNot measured22.1Only Qwen3 235B A22B Thinking 2507 measured
LiveCodeBench (Vals AI)81.9%Not measuredOnly GLM 5 measured
SWE-bench Verified (Vals AI)71.4%Not measuredOnly GLM 5 measured
Vibe Code Bench (Vals AI)23.4%Not measuredOnly GLM 5 measured
Terminal-Bench Hard (Artificial Analysis run)43.2%Not measuredOnly GLM 5 measured
Terminal-Bench52.4%Not measuredOnly GLM 5 measured
WeirdML48.2%41.0%GLM 5
ALE-Bench765.6Not measuredOnly GLM 5 measured
LMArena Text: coding14611424GLM 5
LMArena Text: software and IT14601431GLM 5
LMArena WebDev: React1424Not measuredOnly GLM 5 measured
LMArena WebDev: HTML1450Not measuredOnly GLM 5 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
AA Intelligence Index27.912.7GLM 5
Epoch Capabilities Index145.8Not measuredOnly GLM 5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
AA Agentic IndexNot measured1.3Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: agents building full-stack apps1123Not measuredOnly GLM 5 measured
Design Arena: agents building mobile apps1136Not measuredOnly GLM 5 measured
Design Arena: agents building Android apps1147Not measuredOnly GLM 5 measured
Design Arena: agents building Godot games1144Not measuredOnly GLM 5 measured
Design Arena: HTML slides1098Not measuredOnly GLM 5 measured
τ²-Bench Telecom98.2%Not measuredOnly GLM 5 measured
Vending-Bench 2$4,432-$11GLM 5
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index31
Reasoning benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
GPQA Diamond83.3%Not measuredOnly GLM 5 measured
GPQA Diamond (Artificial Analysis run)82.0%Not measuredOnly GLM 5 measured
Humanity's Last Exam (Artificial Analysis run)29.3%Not measuredOnly GLM 5 measured
GPQA Diamond (Epoch AI run)87.8%80.1%GLM 5
ARC-AGI44.7%Not measuredOnly GLM 5 measured
ARC-AGI-24.9%Not measuredOnly GLM 5 measured
SimpleBench53.2%Not measuredOnly GLM 5 measured
Mystery game puzzlesNot measured9.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: hard prompts14521416GLM 5
LMArena Text: expert14541463Qwen3 235B A22B Thinking 2507
LMArena Text: hard prompts in English14601432GLM 5
Kagi LLM Benchmark75.0%Not measuredOnly GLM 5 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
AIME91.7%Not measuredOnly GLM 5 measured
OTIS Mock AIME80.0%86.7%Qwen3 235B A22B Thinking 2507
LMArena Text: math14401412GLM 5
LMArena Text: mathematical work14511435GLM 5
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
Knowledge benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
MMLU Pro86.0%Not measuredOnly GLM 5 measured
LegalBench (Vals AI)84.1%Not measuredOnly GLM 5 measured
CaseLaw (Vals AI)52.5%Not measuredOnly GLM 5 measured
CorpFin (Vals AI)62.9%Not measuredOnly GLM 5 measured
TaxEval (Vals AI)70.0%Not measuredOnly GLM 5 measured
MedQA (Vals AI)94.3%Not measuredOnly GLM 5 measured
SimpleQA VerifiedNot measured40.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: science14601433GLM 5
LMArena Text: medicine and healthcare14551456Qwen3 235B A22B Thinking 2507
LMArena Text: legal and government14531415GLM 5
LMArena Text: business and finance14301413GLM 5
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
Design Arena: websites12471052GLM 5
Design Arena: UI components1227942GLM 5
Design Arena: game dev1234956GLM 5
Design Arena: data viz1228950GLM 5
Design Arena: 3D1228997GLM 5
Design Arena: all code categories12461032GLM 5
Design Arena: SVG1168Not measuredOnly GLM 5 measured
Design Arena: ASCII art1147Not measuredOnly GLM 5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
General benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
IFBench72.3%Not measuredOnly GLM 5 measured
Long context reasoning (AA-LCR)75.7%Not measuredOnly GLM 5 measured
DTBenchNot measured80.3%Only Qwen3 235B A22B Thinking 2507 measured
LMCANot measured29.3%Only Qwen3 235B A22B Thinking 2507 measured
Fiction.LiveBenchNot measured75.0%Only Qwen3 235B A22B Thinking 2507 measured
Creative writing (Lech Mazur)Not measured82.4%Only Qwen3 235B A22B Thinking 2507 measured
CL-bench18.7%Not measuredOnly GLM 5 measured
LMArena Text14461415GLM 5
LMArena Text: instruction following14281386GLM 5
LMArena Text: creative writing14381384GLM 5
LMArena Text: English14581429GLM 5
LMArena Text: non-English14301397GLM 5
LMArena Text: Chinese15111481GLM 5
LMArena Text: German14471408GLM 5
LMArena Text: Japanese14161386GLM 5
LMArena Text: Korean14231375GLM 5
LMArena Text: French1456Not measuredOnly GLM 5 measured
LMArena Text: Spanish14541389GLM 5
LMArena Text: Russian14361401GLM 5
LMArena Text: Polish14341390GLM 5
LMArena Text: multi-turn14561406GLM 5
LMArena Text: longer queries14461400GLM 5
LMArena Text: writing and language14371388GLM 5
LMArena Text: entertainment and media14261370GLM 5
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
Image generation benchmarks for GLM 5 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5Qwen3 235B A22B Thinking 2507Leader
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 5$0.0026Fits in one request
Qwen3 235B A22B Thinking 2507$0.0022Fits in one request

Qwen3 235B A22B Thinking 2507 costs less

Repository review

50K input + 3K output tokens

GLM 5$0.060Fits in one request
Qwen3 235B A22B Thinking 2507$0.033Fits in one request

Qwen3 235B A22B Thinking 2507 costs less

Agent loop

200K input + 10K output tokens

GLM 5$0.232Exceeds the context window
Qwen3 235B A22B Thinking 2507$0.125Exceeds the context window

Qwen3 235B A22B Thinking 2507 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 5 and Qwen3 235B A22B Thinking 2507
SpecificationZ.ai GLM 5Qwen3 235B A22B Thinking 2507
MakerZ.aiQwen
WeightsOpen weightsOpen weights
ReleasedFebruary 11, 2026July 25, 2025
Context window205K128K
Input $/Mtok$1.00$0.45
Output $/Mtok$3.20$3.50
Coding index41.7Not benchmarked
Independent measurements behind it30
Cost per solved task$0.63Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5 better than Qwen3 235B A22B Thinking 2507 for coding?

Only GLM 5 has a coding score, 41.7 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Thinking 2507 for work measured by LMArena Text: expert or OTIS Mock AIME, where it leads.

Which is cheaper, GLM 5 or Qwen3 235B A22B Thinking 2507?

GLM 5 costs $1.00 per million input tokens and $3.20 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for GLM 5 only.

Which has the bigger context window, GLM 5 or Qwen3 235B A22B Thinking 2507?

GLM 5, with 205K tokens against 128K.

How many benchmarks is the GLM 5 vs Qwen3 235B A22B Thinking 2507 comparison based on?

38 benchmarks have a result for both models as of October 22, 2026. GLM 5's coding index rests on 3 independent benchmarks and Qwen3 235B A22B Thinking 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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