Enter opens the highlighted result. Esc closes.

GLM 5.3 Flash vs Qwen3 VL 235B A22B Instruct

GLM 5.3 Flash leads Qwen3 VL 235B A22B Instruct on the Artificial Analysis Intelligence Index, 41.8 to 9.9, and GLM 5.3 Flash costs 3.8x less per output token ($0.50 vs $1.90 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace Qwen3 VL 235B A22B Instruct
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
40
Qwen3 VL 235B A22B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.90
0
vs boards won of 40 shared

GLM 5.3 Flash or Qwen3 VL 235B A22B Instruct: which to pick

Only GLM 5.3 Flash has a coding score, 57.7 on the Vibe Coding Index; Qwen3 VL 235B A22B Instruct has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved taskModel BQwen3 VL 235B A22B InstructQwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
40
GLM 5.3 Flash only
62
Qwen3 VL 235B A22B Instruct only
9
Like-for-like categories
6 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 VL 235B A22B Instruct not benchmarked.
Widest category
Intelligence, 31.9 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: GLM 5.3 Flash 41.8 against Qwen3 VL 235B A22B Instruct 9.9, 31.9 points apart on a 0 to 100 scale.
Output price
GLM 5.3 Flash $0.50 against Qwen3 VL 235B A22B Instruct $1.90 per million output tokens, 3.8x apart.
Context window
GLM 5.3 Flash takes 1.05M tokens, Qwen3 VL 235B A22B Instruct 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 5.3 FlashBarsQwen3 VL 235B A22B InstructTies
Coding20
Intelligence10
Reasoning70
Math20
Knowledge40
General240
All shared boards400
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
LiveBench coding80.6%Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev1607Not measuredOnly GLM 5.3 Flash measured
AA Coding Index71.5Not measuredOnly GLM 5.3 Flash measured
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
LiveCodeBench (Artificial Analysis run)Not measured64.6%Only Qwen3 VL 235B A22B Instruct measured
SciCode51.6%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench Hard (Artificial Analysis run)Not measured11.4%Only Qwen3 VL 235B A22B Instruct measured
FrontierCode31.8%Not measuredOnly GLM 5.3 Flash measured
FrontierSWE18.1%Not measuredOnly GLM 5.3 Flash measured
ALE-Bench303.6Not measuredOnly GLM 5.3 Flash measured
LMArena Text: coding15071438GLM 5.3 Flash
LMArena Text: software and IT15001442GLM 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 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
AA Intelligence Index41.89.9GLM 5.3 Flash
Epoch Capabilities Index153.1Not measuredOnly GLM 5.3 Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Agentic work benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
AA Agentic Index50.9Not measuredOnly GLM 5.3 Flash measured
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
τ²-Bench TelecomNot measured54.1%Only Qwen3 VL 235B A22B Instruct measured
APEX-Agents52.8%Not measuredOnly GLM 5.3 Flash measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
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%77.2%GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)39.9%11.9%GLM 5.3 Flash
GPQA Diamond (Epoch AI run)90.2%Not measuredOnly GLM 5.3 Flash measured
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%Not measuredOnly GLM 5.3 Flash measured
LMArena Text: hard prompts14901428GLM 5.3 Flash
LMArena Text: expert15111442GLM 5.3 Flash
LMArena Text: hard prompts in English14881439GLM 5.3 Flash
LMArena Vision: diagrams13171255GLM 5.3 Flash
LMArena Vision: homework13181277GLM 5.3 Flash
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
AA Math IndexNot measured88.3Only Qwen3 VL 235B A22B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured88.3%Only Qwen3 VL 235B A22B Instruct measured
OTIS Mock AIME93.9%Not measuredOnly GLM 5.3 Flash measured
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: math15031425GLM 5.3 Flash
LMArena Text: mathematical work14971419GLM 5.3 Flash
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
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
MMLU Pro (Artificial Analysis run)Not measured83.6%Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: science14841444GLM 5.3 Flash
LMArena Text: medicine and healthcare14751431GLM 5.3 Flash
LMArena Text: legal and government14731438GLM 5.3 Flash
LMArena Text: business and finance14601433GLM 5.3 Flash
Neither model has a result on the other 10 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
Design Arena: websites1272Not measuredOnly GLM 5.3 Flash measured
Design Arena: UI components1316Not measuredOnly GLM 5.3 Flash measured
Design Arena: game dev1278Not measuredOnly GLM 5.3 Flash measured
Design Arena: data viz1262Not measuredOnly GLM 5.3 Flash measured
Design Arena: 3D1316Not measuredOnly GLM 5.3 Flash measured
Design Arena: all code categories1282Not measuredOnly GLM 5.3 Flash measured
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 index240
General benchmarks for GLM 5.3 Flash and Qwen3 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
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
IFBenchNot measured56.5%Only Qwen3 VL 235B A22B Instruct measured
Long context reasoning (AA-LCR)80.0%63.7%GLM 5.3 Flash
Surface Evolver Bench52.5%Not measuredOnly GLM 5.3 Flash measured
LMArena Text14711420GLM 5.3 Flash
LMArena Text: instruction following14781406GLM 5.3 Flash
LMArena Text: creative writing14411366GLM 5.3 Flash
LMArena Vision12941247GLM 5.3 Flash
LMArena Text: English14741429GLM 5.3 Flash
LMArena Text: non-English14621405GLM 5.3 Flash
LMArena Text: Chinese15311463GLM 5.3 Flash
LMArena Text: German14621424GLM 5.3 Flash
LMArena Text: Japanese14441385GLM 5.3 Flash
LMArena Text: Korean14361394GLM 5.3 Flash
LMArena Text: French14911452GLM 5.3 Flash
LMArena Text: Spanish14751428GLM 5.3 Flash
LMArena Text: Russian14651408GLM 5.3 Flash
LMArena Text: Polish14501419GLM 5.3 Flash
LMArena Text: multi-turn14691428GLM 5.3 Flash
LMArena Text: longer queries14811419GLM 5.3 Flash
LMArena Text: writing and language14551392GLM 5.3 Flash
LMArena Text: entertainment and media14401368GLM 5.3 Flash
LMArena Vision: English12951256GLM 5.3 Flash
LMArena Vision: Chinese13631283GLM 5.3 Flash
LMArena Vision: reading text12991253GLM 5.3 Flash
LMArena Vision: humor12791209GLM 5.3 Flash
LMArena Vision: captioningNot measured1281Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: recognizing thingsNot measured1249Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: creative writing12701220GLM 5.3 Flash
Neither model has a result on the other 15 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 VL 235B A22B Instruct
BenchmarkGLM 5.3 FlashQwen3 VL 235B A22B InstructLeader
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 VL 235B A22B Instruct$0.0012Fits 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 VL 235B A22B Instruct$0.016Fits 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 VL 235B A22B Instruct$0.061Fits in one request

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 VL 235B A22B Instruct
SpecificationZ.ai GLM 5.3 FlashQwen3 VL 235B A22B Instruct
MakerZ.aiQwen
WeightsOpen weightsOpen weights
ReleasedAugust 26, 2026September 23, 2025
Context window1.05M262K
Input $/Mtok$0.15$0.21
Output $/Mtok$0.50$1.90
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 VL 235B A22B Instruct for coding?

Only GLM 5.3 Flash has a coding score, 57.7 on the Vibe Coding Index; Qwen3 VL 235B A22B Instruct has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GLM 5.3 Flash or Qwen3 VL 235B A22B Instruct?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Qwen3 VL 235B A22B Instruct costs $0.21 and $1.90. Cost per solved task is known for GLM 5.3 Flash only.

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

GLM 5.3 Flash, with 1.05M tokens against 262K.

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

40 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 VL 235B A22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next