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GLM 5.3 Flash vs Qwen3.7 Plus

GLM 5.3 Flash leads Qwen3.7 Plus on coding, 57.7 to 33.2 on the Vibe Coding Index, and GLM 5.3 Flash costs 2.6x less per output token ($0.50 vs $1.28 per million). Updated October 21, 2026; 65 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace Qwen3.7 Plus
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
41.8
Output $/M
$0.50
60
Qwen3.7 PlusQwen
Coding
33.2
Overall
25.2
Output $/M
$1.28
5
vs boards won of 65 shared

GLM 5.3 Flash or Qwen3.7 Plus: which to pick

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus.

Pick Qwen3.7 Plus for work measured by Vibe Code Bench (Vals AI) or SkillsBench (Vals AI), where it leads.

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
65
GLM 5.3 Flash only
37
Qwen3.7 Plus only
10
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, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Agentic work, 21.9 points apart on average over 5 shared benchmarks.
Widest single gap
AA Agentic Index: GLM 5.3 Flash 50.9 against Qwen3.7 Plus 17.5, 33.4 points apart on a 0 to 100 scale.
Output price
GLM 5.3 Flash $0.50 against Qwen3.7 Plus $1.28 per million output tokens, 2.6x apart.
Context window
GLM 5.3 Flash takes 1.05M tokens, Qwen3.7 Plus 1M.

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 FlashBarsQwen3.7 PlusTies
Coding72
Intelligence20
Agentic work50
Reasoning81
Math40
Knowledge40
Web design71
General231
All shared boards605
CodingLike-for-likeSix of these boards feed the Vibe Coding Index72
Coding benchmarks for GLM 5.3 Flash and Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
LiveBench coding80.6%Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev1607Not measuredOnly GLM 5.3 Flash measured
AA Coding Index71.555.9GLM 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%46.4%Qwen3.7 Plus
Code migration (Vals AI)20.5%12.9%GLM 5.3 Flash
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%52.8%GLM 5.3 Flash
Vibe Code Bench 1-100 (Vals AI)16.0%Not measuredOnly GLM 5.3 Flash measured
SkillsBench (Vals AI)40.2%54.3%Qwen3.7 Plus
CyberBench (Vals AI)67.9%Not measuredOnly GLM 5.3 Flash measured
SciCode51.6%46.1%GLM 5.3 Flash
Terminal-Bench Hard (Artificial Analysis run)Not measured47.0%Only Qwen3.7 Plus measured
FrontierCode31.8%10.2%GLM 5.3 Flash
FrontierSWE18.1%Not measuredOnly GLM 5.3 Flash measured
ALE-Bench303.6Not measuredOnly GLM 5.3 Flash measured
LMArena Text: coding15071473GLM 5.3 Flash
LMArena Text: software and IT15001473GLM 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 index20
Intelligence benchmarks for GLM 5.3 Flash and Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
AA Intelligence Index41.825.2GLM 5.3 Flash
Epoch Capabilities Index153.1147.0GLM 5.3 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
Agentic work benchmarks for GLM 5.3 Flash and Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
AA Agentic Index50.917.5GLM 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%38.2%GLM 5.3 Flash
Tax Agent Bench (Vals AI)31.6%10.5%GLM 5.3 Flash
Legal Research Bench (Vals AI)45.2%16.4%GLM 5.3 Flash
Harvey's Legal Agent Benchmark (Vals AI)10.4%Not measuredOnly GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)55.9%49.3%GLM 5.3 Flash
Terminal-Bench-Science (Vals AI)2.9%Not measuredOnly GLM 5.3 Flash measured
τ²-Bench TelecomNot measured93.0%Only Qwen3.7 Plus measured
APEX-Agents52.8%Not measuredOnly GLM 5.3 Flash measured
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index81
Reasoning benchmarks for GLM 5.3 Flash and Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
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%90.0%GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)39.9%35.6%GLM 5.3 Flash
GPQA Diamond (Epoch AI run)90.2%87.9%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%17.0%Qwen3.7 Plus
LMArena Text: hard prompts14901460GLM 5.3 Flash
LMArena Text: expert15111466GLM 5.3 Flash
LMArena Text: hard prompts in English14881460GLM 5.3 Flash
LMArena Vision: diagrams13171292GLM 5.3 Flash
LMArena Vision: homework13181295GLM 5.3 Flash
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for GLM 5.3 Flash and Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
OTIS Mock AIME93.9%93.3%GLM 5.3 Flash
FrontierMath, tiers 1 to 355.8%34.4%GLM 5.3 Flash
FrontierMath, tier 417.1%Not measuredOnly GLM 5.3 Flash measured
ProofBench21.0%Not measuredOnly GLM 5.3 Flash measured
LMArena Text: math15031467GLM 5.3 Flash
LMArena Text: mathematical work14971470GLM 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 Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
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
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
LMArena Text: science14841464GLM 5.3 Flash
LMArena Text: medicine and healthcare14751464GLM 5.3 Flash
LMArena Text: legal and government14731451GLM 5.3 Flash
LMArena Text: business and finance14601435GLM 5.3 Flash
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index71
Web design benchmarks for GLM 5.3 Flash and Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
Design Arena: websites12721269GLM 5.3 Flash
Design Arena: UI components13161261GLM 5.3 Flash
Design Arena: game dev12781262GLM 5.3 Flash
Design Arena: data viz12611276Qwen3.7 Plus
Design Arena: 3D13161239GLM 5.3 Flash
Design Arena: all code categories12821269GLM 5.3 Flash
Design Arena: SVG12841208GLM 5.3 Flash
Design Arena: ASCII art12681143GLM 5.3 Flash
LiveBench design77.2%Not measuredOnly GLM 5.3 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index231
General benchmarks for GLM 5.3 Flash and Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
Vals Index50.9%Not measuredOnly GLM 5.3 Flash measured
LiveBench data analysis76.4%Not measuredOnly GLM 5.3 Flash measured
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
MedScribe (Vals AI)88.9%Not measuredOnly GLM 5.3 Flash measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBenchNot measured78.0%Only Qwen3.7 Plus measured
Long context reasoning (AA-LCR)80.0%73.0%GLM 5.3 Flash
DTBenchNot measured84.0%Only Qwen3.7 Plus measured
LMCANot measured37.6%Only Qwen3.7 Plus measured
Surface Evolver Bench52.5%Not measuredOnly GLM 5.3 Flash measured
LMArena Text14711454GLM 5.3 Flash
LMArena Text: instruction following14781439GLM 5.3 Flash
LMArena Text: creative writing14411438GLM 5.3 Flash
LMArena Vision12941278GLM 5.3 Flash
LMArena Text: English14741458GLM 5.3 Flash
LMArena Text: non-English14621445GLM 5.3 Flash
LMArena Text: Chinese15311509GLM 5.3 Flash
LMArena Text: German14621471Qwen3.7 Plus
LMArena Text: Japanese14441412GLM 5.3 Flash
LMArena Text: Korean14361413GLM 5.3 Flash
LMArena Text: French14911472GLM 5.3 Flash
LMArena Text: Spanish14751457GLM 5.3 Flash
LMArena Text: Russian14651457GLM 5.3 Flash
LMArena Text: Polish14501449GLM 5.3 Flash
LMArena Text: multi-turn14691459GLM 5.3 Flash
LMArena Text: longer queries14811454GLM 5.3 Flash
LMArena Text: writing and language14551437GLM 5.3 Flash
LMArena Text: entertainment and media14401422GLM 5.3 Flash
LMArena Vision: English12951280GLM 5.3 Flash
LMArena Vision: Chinese13631332GLM 5.3 Flash
LMArena Vision: reading text12991288GLM 5.3 Flash
LMArena Vision: humor12791261GLM 5.3 Flash
LMArena Vision: creative writing12701258GLM 5.3 Flash
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 12 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 Qwen3.7 Plus
BenchmarkGLM 5.3 FlashQwen3.7 PlusLeader
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
Qwen3.7 Plus$0.0010Fits 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
Qwen3.7 Plus$0.020Fits 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
Qwen3.7 Plus$0.077Fits 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 Qwen3.7 Plus
SpecificationZ.ai GLM 5.3 FlashQwen3.7 Plus
MakerZ.aiQwen
WeightsOpen weightsNo public weights listed
ReleasedAugust 26, 2026June 3, 2026
Context window1.05M1M
Input $/Mtok$0.15$0.32
Output $/Mtok$0.50$1.28
Coding index57.733.2
Independent measurements behind it62
Cost per solved task$0.02Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Flash better than Qwen3.7 Plus for coding?

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus. Pick Qwen3.7 Plus for work measured by Vibe Code Bench (Vals AI) or SkillsBench (Vals AI), where it leads.

Which is cheaper, GLM 5.3 Flash or Qwen3.7 Plus?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for GLM 5.3 Flash only.

Which has the bigger context window, GLM 5.3 Flash or Qwen3.7 Plus?

GLM 5.3 Flash, with 1.05M tokens against 1M.

How many benchmarks is the GLM 5.3 Flash vs Qwen3.7 Plus comparison based on?

65 benchmarks have a result for both models as of October 21, 2026. GLM 5.3 Flash's coding index rests on 6 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/glm-5-3-flash-vs-qwen3-7-plus">LLMBenchmark.ai, GLM 5.3 Flash vs Qwen3.7 Plus</a></p>