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GLM 5.3 Flash vs Qwen3 235B A22B Thinking 2507

GLM 5.3 Flash leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 41.8 to 12.7, and GLM 5.3 Flash costs 7.0x less per output token ($0.50 vs $3.50 per million). Updated October 22, 2026; 39 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace Qwen3 235B A22B Thinking 2507
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
38
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
1
vs boards won of 39 shared

GLM 5.3 Flash or Qwen3 235B A22B Thinking 2507: which to pick

Only GLM 5.3 Flash has a coding score, 57.7 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 Mystery game puzzles, where it leads.

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved taskModel BQwen3 235B A22B Thinking 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
39
GLM 5.3 Flash only
63
Qwen3 235B A22B Thinking 2507 only
7
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 5.3 Flash 57.7 from 6 benchmarks, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
Agentic work, 49.6 points apart on average over 1 shared benchmark.
Widest single gap
AA Agentic Index: GLM 5.3 Flash 50.9 against Qwen3 235B A22B Thinking 2507 1.3, 49.6 points apart on a 0 to 100 scale.
Output price
GLM 5.3 Flash $0.50 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 7.0x apart.
Context window
GLM 5.3 Flash takes 1.05M 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 5.3 FlashBarsQwen3 235B A22B Thinking 2507Ties
Coding30
Intelligence10
Agentic work10
Reasoning41
Math30
Knowledge40
Web design60
General160
All shared boards381
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
LiveBench coding80.6%Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev1607Not measuredOnly GLM 5.3 Flash measured
AA Coding Index71.522.1GLM 5.3 Flash
LiveCodeBench (Vals AI)80.5%Not measuredOnly GLM 5.3 Flash measured
SWE-bench Verified (Vals AI)92.0%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench 4 (Vals AI)37.4%Not measuredOnly GLM 5.3 Flash measured
Vibe Code Bench (Vals AI)30.8%Not measuredOnly GLM 5.3 Flash measured
Code migration (Vals AI)20.5%Not measuredOnly GLM 5.3 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.3 Flash measured
IOI (Vals AI)52.5%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)62.9%Not measuredOnly GLM 5.3 Flash measured
Vibe Code Bench 1-100 (Vals AI)16.0%Not measuredOnly GLM 5.3 Flash measured
SkillsBench (Vals AI)40.2%Not measuredOnly GLM 5.3 Flash measured
CyberBench (Vals AI)67.9%Not measuredOnly GLM 5.3 Flash measured
SciCode51.6%Not measuredOnly GLM 5.3 Flash measured
FrontierCode31.8%Not measuredOnly GLM 5.3 Flash measured
FrontierSWE18.1%Not measuredOnly GLM 5.3 Flash measured
WeirdMLNot measured41.0%Only Qwen3 235B A22B Thinking 2507 measured
ALE-Bench303.6Not measuredOnly GLM 5.3 Flash measured
LMArena Text: coding15071424GLM 5.3 Flash
LMArena Text: software and IT15001431GLM 5.3 Flash
LMArena WebDev: React1624Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev: HTML1577Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev: from an image1578Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
AA Intelligence Index41.812.7GLM 5.3 Flash
Epoch Capabilities Index153.1Not measuredOnly GLM 5.3 Flash measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
AA Agentic Index50.91.3GLM 5.3 Flash
LiveBench research70.1%Not measuredOnly GLM 5.3 Flash measured
LiveBench browser84.0%Not measuredOnly GLM 5.3 Flash measured
LiveBench long agentic28.4%Not measuredOnly GLM 5.3 Flash measured
SREBench (Vals AI)0.8%Not measuredOnly GLM 5.3 Flash measured
Finance Agent (Vals AI)57.9%Not measuredOnly GLM 5.3 Flash measured
Tax Agent Bench (Vals AI)31.6%Not measuredOnly GLM 5.3 Flash measured
Legal Research Bench (Vals AI)45.2%Not measuredOnly GLM 5.3 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)10.4%Not measuredOnly GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)55.9%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench-Science (Vals AI)2.9%Not measuredOnly GLM 5.3 Flash measured
APEX-Agents52.8%Not measuredOnly GLM 5.3 Flash measured
Vending-Bench 2Not measured-$11Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
GPQA Diamond86.4%Not measuredOnly GLM 5.3 Flash measured
LiveBench reasoning77.6%Not measuredOnly GLM 5.3 Flash measured
MMMU Pro (Vals AI)86.0%Not measuredOnly GLM 5.3 Flash measured
GPQA Diamond (Artificial Analysis run)91.2%Not measuredOnly GLM 5.3 Flash measured
Humanity's Last Exam (Artificial Analysis run)39.9%Not measuredOnly GLM 5.3 Flash measured
GPQA Diamond (Epoch AI run)90.2%80.1%GLM 5.3 Flash
ARC-AGI91.0%Not measuredOnly GLM 5.3 Flash measured
ARC-AGI-265.8%Not measuredOnly GLM 5.3 Flash measured
Chess puzzles21.0%Not measuredOnly GLM 5.3 Flash measured
Mystery game puzzles8.0%9.0%Qwen3 235B A22B Thinking 2507
LMArena Text: hard prompts14901416GLM 5.3 Flash
LMArena Text: expert15111463GLM 5.3 Flash
LMArena Text: hard prompts in English14881432GLM 5.3 Flash
LMArena Vision: diagrams1317Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: homework1318Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
OTIS Mock AIME93.9%86.7%GLM 5.3 Flash
FrontierMath, tiers 1 to 355.8%Not measuredOnly GLM 5.3 Flash measured
FrontierMath, tier 417.1%Not measuredOnly GLM 5.3 Flash measured
ProofBench21.0%Not measuredOnly GLM 5.3 Flash measured
LMArena Text: math15031412GLM 5.3 Flash
LMArena Text: mathematical work14971435GLM 5.3 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
MMLU Pro86.1%Not measuredOnly GLM 5.3 Flash measured
LegalBench (Vals AI)83.9%Not measuredOnly GLM 5.3 Flash measured
TaxEval (Vals AI)75.6%Not measuredOnly GLM 5.3 Flash measured
SimpleQA VerifiedNot measured40.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: science14841433GLM 5.3 Flash
LMArena Text: medicine and healthcare14751456GLM 5.3 Flash
LMArena Text: legal and government14731415GLM 5.3 Flash
LMArena Text: business and finance14601413GLM 5.3 Flash
Neither model has a result on the other 10 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
Design Arena: websites12721052GLM 5.3 Flash
Design Arena: UI components1316942GLM 5.3 Flash
Design Arena: game dev1278956GLM 5.3 Flash
Design Arena: data viz1262950GLM 5.3 Flash
Design Arena: 3D1316997GLM 5.3 Flash
Design Arena: all code categories12821032GLM 5.3 Flash
Design Arena: SVG1285Not measuredOnly GLM 5.3 Flash measured
Design Arena: ASCII art1267Not measuredOnly GLM 5.3 Flash measured
LiveBench design77.2%Not measuredOnly GLM 5.3 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
General benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 235B A22B Thinking 2507Leader
Vals Index50.9%Not measuredOnly GLM 5.3 Flash measured
LiveBench data analysis76.4%Not measuredOnly GLM 5.3 Flash measured
MedScribe (Vals AI)88.9%Not measuredOnly GLM 5.3 Flash measured
Long context reasoning (AA-LCR)80.0%Not measuredOnly GLM 5.3 Flash 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
Surface Evolver Bench52.5%Not measuredOnly GLM 5.3 Flash measured
LMArena Text14711415GLM 5.3 Flash
LMArena Text: instruction following14781386GLM 5.3 Flash
LMArena Text: creative writing14411384GLM 5.3 Flash
LMArena Vision1294Not measuredOnly GLM 5.3 Flash measured
LMArena Text: English14741429GLM 5.3 Flash
LMArena Text: non-English14621397GLM 5.3 Flash
LMArena Text: Chinese15311481GLM 5.3 Flash
LMArena Text: German14621408GLM 5.3 Flash
LMArena Text: Japanese14441386GLM 5.3 Flash
LMArena Text: Korean14361375GLM 5.3 Flash
LMArena Text: French1491Not measuredOnly GLM 5.3 Flash measured
LMArena Text: Spanish14751389GLM 5.3 Flash
LMArena Text: Russian14651401GLM 5.3 Flash
LMArena Text: Polish14501390GLM 5.3 Flash
LMArena Text: multi-turn14691406GLM 5.3 Flash
LMArena Text: longer queries14811400GLM 5.3 Flash
LMArena Text: writing and language14551388GLM 5.3 Flash
LMArena Text: entertainment and media14401370GLM 5.3 Flash
LMArena Vision: English1295Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: Chinese1363Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: reading text1299Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: humor1279Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: creative writing1270Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.3 Flash and Qwen3 235B A22B Thinking 2507
BenchmarkGLM 5.3 FlashQwen3 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 5.3 Flash$0.0004Fits in one request
Qwen3 235B A22B Thinking 2507$0.0022Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Flash$0.0090Fits in one request
Qwen3 235B A22B Thinking 2507$0.033Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Flash$0.035Fits in one request
Qwen3 235B A22B Thinking 2507$0.125Exceeds the context window

GLM 5.3 Flash 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 5.3 Flash and Qwen3 235B A22B Thinking 2507
SpecificationZ.ai GLM 5.3 FlashQwen3 235B A22B Thinking 2507
MakerZ.aiQwen
WeightsOpen weightsOpen weights
ReleasedAugust 26, 2026July 25, 2025
Context window1.05M128K
Input $/Mtok$0.15$0.45
Output $/Mtok$0.50$3.50
Coding index57.7Not benchmarked
Independent measurements behind it60
Cost per solved task$0.02Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Flash better than Qwen3 235B A22B Thinking 2507 for coding?

Only GLM 5.3 Flash has a coding score, 57.7 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 Mystery game puzzles, where it leads.

Which is cheaper, GLM 5.3 Flash or Qwen3 235B A22B Thinking 2507?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for GLM 5.3 Flash only.

Which has the bigger context window, GLM 5.3 Flash or Qwen3 235B A22B Thinking 2507?

GLM 5.3 Flash, with 1.05M tokens against 128K.

How many benchmarks is the GLM 5.3 Flash vs Qwen3 235B A22B Thinking 2507 comparison based on?

39 benchmarks have a result for both models as of October 22, 2026. GLM 5.3 Flash's coding index rests on 6 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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