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GLM 5.1 vs Qwen3 235B A22B Thinking 2507

GLM 5.1 leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 26.1 to 12.7, and Qwen3 235B A22B Thinking 2507 costs 1.3x less per output token ($3.50 vs $4.40 per million). Updated October 22, 2026; 41 benchmarks have a result for both.

Replace GLM 5.1 Replace Qwen3 235B A22B Thinking 2507
GLM 5.1Z.ai
Coding
49.2
Overall
57.5
Output $/M
$4.40
40
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
1
vs boards won of 41 shared

GLM 5.1 or Qwen3 235B A22B Thinking 2507: which to pick

Only GLM 5.1 has a coding score, 49.2 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 output tokens 1.3x cheaper ($3.50 vs $4.40 per million) and work measured by SimpleQA Verified, where it leads.

Model AGLM 5.1Z.ai49.2/1003 independent benchmarks$0.60 per solved taskModel BQwen3 235B A22B Thinking 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
41
GLM 5.1 only
50
Qwen3 235B A22B Thinking 2507 only
5
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 5.1 49.2 from 3 benchmarks, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
Web design, 39.3 points apart on average over 6 shared benchmarks.
Widest single gap
Design Arena: data viz: GLM 5.1 1366 against Qwen3 235B A22B Thinking 2507 950, 52.0 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 1.3x apart.
Context window
GLM 5.1 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 5.1BarsQwen3 235B A22B Thinking 2507Ties
Coding40
Intelligence10
Agentic work20
Reasoning40
Math30
Knowledge41
Web design60
General160
All shared boards401
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for GLM 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
LMArena WebDev1508Not measuredOnly GLM 5.1 measured
AA Coding Index55.822.1GLM 5.1
LiveCodeBench (Vals AI)81.4%Not measuredOnly GLM 5.1 measured
SWE-bench Verified (Vals AI)76.4%Not measuredOnly GLM 5.1 measured
Vibe Code Bench (Vals AI)31.5%Not measuredOnly GLM 5.1 measured
Code migration (Vals AI)25.8%Not measuredOnly GLM 5.1 measured
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)56.9%Not measuredOnly GLM 5.1 measured
SciCode44.8%Not measuredOnly GLM 5.1 measured
Terminal-Bench Hard (Artificial Analysis run)43.2%Not measuredOnly GLM 5.1 measured
WeirdML57.1%41.0%GLM 5.1
ALE-Bench887.1Not measuredOnly GLM 5.1 measured
LMArena Text: coding14851424GLM 5.1
LMArena Text: software and IT14841431GLM 5.1
LMArena WebDev: React1505Not measuredOnly GLM 5.1 measured
LMArena WebDev: HTML1508Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
AA Intelligence Index26.112.7GLM 5.1
Epoch Capabilities Index149.8Not measuredOnly GLM 5.1 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for GLM 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
AA Agentic Index23.91.3GLM 5.1
Design Arena: agents building web apps1175Not measuredOnly GLM 5.1 measured
Design Arena: agents building full-stack apps1167Not measuredOnly GLM 5.1 measured
Design Arena: agents building mobile apps1160Not measuredOnly GLM 5.1 measured
Design Arena: agents building Android apps1181Not measuredOnly GLM 5.1 measured
Design Arena: agents building Godot games1053Not measuredOnly GLM 5.1 measured
Design Arena: agents building games1164Not measuredOnly GLM 5.1 measured
Design Arena: HTML slides1109Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1162Not measuredOnly GLM 5.1 measured
Design Arena: spreadsheets1315Not measuredOnly GLM 5.1 measured
Finance Agent (Vals AI)44.8%Not measuredOnly GLM 5.1 measured
Legal Research Bench (Vals AI)27.9%Not measuredOnly GLM 5.1 measured
τ²-Bench Telecom97.7%Not measuredOnly GLM 5.1 measured
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
Vending-Bench 2$5,634-$11GLM 5.1
MCP Atlas75.6%Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for GLM 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
GPQA Diamond84.5%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Artificial Analysis run)86.8%Not measuredOnly GLM 5.1 measured
Humanity's Last Exam (Artificial Analysis run)30.1%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Epoch AI run)89.9%80.1%GLM 5.1
SimpleBench55.1%Not measuredOnly GLM 5.1 measured
Chess puzzles20.0%Not measuredOnly GLM 5.1 measured
Mystery game puzzlesNot measured9.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: hard prompts14731416GLM 5.1
LMArena Text: expert14781463GLM 5.1
LMArena Text: hard prompts in English14821432GLM 5.1
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for GLM 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
AIME91.9%Not measuredOnly GLM 5.1 measured
OTIS Mock AIME93.3%86.7%GLM 5.1
FrontierMath, tiers 1 to 336.8%Not measuredOnly GLM 5.1 measured
ProofBench22.2%Not measuredOnly GLM 5.1 measured
LMArena Text: math14731412GLM 5.1
LMArena Text: mathematical work14701435GLM 5.1
MathArena20.1%Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for GLM 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
MMLU Pro86.9%Not measuredOnly GLM 5.1 measured
LegalBench (Vals AI)84.4%Not measuredOnly GLM 5.1 measured
CaseLaw (Vals AI)51.5%Not measuredOnly GLM 5.1 measured
CorpFin (Vals AI)64.5%Not measuredOnly GLM 5.1 measured
TaxEval (Vals AI)71.2%Not measuredOnly GLM 5.1 measured
MedCode (Vals AI)41.6%Not measuredOnly GLM 5.1 measured
SimpleQA Verified34.0%40.4%Qwen3 235B A22B Thinking 2507
LMArena Text: science14781433GLM 5.1
LMArena Text: medicine and healthcare14741456GLM 5.1
LMArena Text: legal and government14651415GLM 5.1
LMArena Text: business and finance14521413GLM 5.1
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for GLM 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
Design Arena: websites12901052GLM 5.1
Design Arena: UI components1292942GLM 5.1
Design Arena: game dev1264956GLM 5.1
Design Arena: data viz1366950GLM 5.1
Design Arena: 3D1336997GLM 5.1
Design Arena: all code categories12681032GLM 5.1
Design Arena: SVG1217Not measuredOnly GLM 5.1 measured
Design Arena: ASCII art1141Not measuredOnly GLM 5.1 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 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 235B A22B Thinking 2507Leader
Public Benefits Bench (Vals AI)61.8%Not measuredOnly GLM 5.1 measured
MedScribe (Vals AI)72.3%Not measuredOnly GLM 5.1 measured
IFBench76.3%Not measuredOnly GLM 5.1 measured
Long context reasoning (AA-LCR)73.7%Not measuredOnly GLM 5.1 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
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text14631415GLM 5.1
LMArena Text: instruction following14531386GLM 5.1
LMArena Text: creative writing14531384GLM 5.1
LMArena Text: English14761429GLM 5.1
LMArena Text: non-English14481397GLM 5.1
LMArena Text: Chinese15151481GLM 5.1
LMArena Text: German14671408GLM 5.1
LMArena Text: Japanese14351386GLM 5.1
LMArena Text: Korean14241375GLM 5.1
LMArena Text: French1470Not measuredOnly GLM 5.1 measured
LMArena Text: Spanish14681389GLM 5.1
LMArena Text: Russian14541401GLM 5.1
LMArena Text: Polish14491390GLM 5.1
LMArena Text: multi-turn14731406GLM 5.1
LMArena Text: longer queries14671400GLM 5.1
LMArena Text: writing and language14541388GLM 5.1
LMArena Text: entertainment and media14421370GLM 5.1
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 5.1 and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.1Qwen3 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 5.1$0.0036Fits 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 5.1$0.083Fits 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 5.1$0.324Exceeds 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 5.1 and Qwen3 235B A22B Thinking 2507
SpecificationZ.ai GLM 5.1Qwen3 235B A22B Thinking 2507
MakerZ.aiQwen
WeightsOpen weightsOpen weights
ReleasedApril 7, 2026July 25, 2025
Context window205K128K
Input $/Mtok$1.40$0.45
Output $/Mtok$4.40$3.50
Coding index49.2Not benchmarked
Independent measurements behind it30
Cost per solved task$0.60Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than Qwen3 235B A22B Thinking 2507 for coding?

Only GLM 5.1 has a coding score, 49.2 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 output tokens 1.3x cheaper ($3.50 vs $4.40 per million) and work measured by SimpleQA Verified, where it leads.

Which is cheaper, GLM 5.1 or Qwen3 235B A22B Thinking 2507?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for GLM 5.1 only.

Which has the bigger context window, GLM 5.1 or Qwen3 235B A22B Thinking 2507?

GLM 5.1, with 205K tokens against 128K.

How many benchmarks is the GLM 5.1 vs Qwen3 235B A22B Thinking 2507 comparison based on?

41 benchmarks have a result for both models as of October 22, 2026. GLM 5.1'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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