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GLM 4.7 Flash vs Qwen3.7 Plus

Qwen3.7 Plus leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 25.2 to 14.9, and GLM 4.7 Flash costs 3.2x less per output token ($0.40 vs $1.28 per million). Updated October 21, 2026; 43 benchmarks have a result for both.

Replace GLM 4.7 Flash Replace Qwen3.7 Plus
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
1
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
42
vs boards won of 43 shared

GLM 4.7 Flash or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.

Pick GLM 4.7 Flash for output tokens 3.2x cheaper ($0.40 vs $1.28 per million) and work measured by τ²-Bench Telecom, where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
43
GLM 4.7 Flash only
0
Qwen3.7 Plus only
32
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 4.7 Flash not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Math, 23.5 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GLM 4.7 Flash 58.3% against Qwen3.7 Plus 93.3%, 35.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against Qwen3.7 Plus $1.28 per million output tokens, 3.2x apart.
Context window
GLM 4.7 Flash takes 200K 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 4.7 FlashBarsQwen3.7 PlusTies
Coding03
Intelligence01
Agentic work10
Reasoning06
Math03
Knowledge04
Web design07
General018
All shared boards142
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
AA Coding IndexNot measured55.9Only Qwen3.7 Plus measured
Vibe Code Bench (Vals AI)Not measured46.4%Only Qwen3.7 Plus measured
Code migration (Vals AI)Not measured12.9%Only Qwen3.7 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
SciCodeNot measured46.1%Only Qwen3.7 Plus measured
Terminal-Bench Hard (Artificial Analysis run)22.0%47.0%Qwen3.7 Plus
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
LMArena Text: coding13821473Qwen3.7 Plus
LMArena Text: software and IT13891473Qwen3.7 Plus
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
AA Intelligence Index14.925.2Qwen3.7 Plus
Epoch Capabilities IndexNot measured147.0Only Qwen3.7 Plus measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
AA Agentic IndexNot measured17.5Only Qwen3.7 Plus measured
Finance Agent (Vals AI)Not measured38.2%Only Qwen3.7 Plus measured
Tax Agent Bench (Vals AI)Not measured10.5%Only Qwen3.7 Plus measured
Legal Research Bench (Vals AI)Not measured16.4%Only Qwen3.7 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured49.3%Only Qwen3.7 Plus measured
τ²-Bench Telecom98.8%93.0%GLM 4.7 Flash
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
GPQA Diamond (Artificial Analysis run)58.1%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)7.6%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)60.5%87.9%Qwen3.7 Plus
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts13561460Qwen3.7 Plus
LMArena Text: expert13571466Qwen3.7 Plus
LMArena Text: hard prompts in English13691460Qwen3.7 Plus
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
OTIS Mock AIME58.3%93.3%Qwen3.7 Plus
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
LMArena Text: math13551467Qwen3.7 Plus
LMArena Text: mathematical work13691470Qwen3.7 Plus
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
LMArena Text: science13581464Qwen3.7 Plus
LMArena Text: medicine and healthcare13431464Qwen3.7 Plus
LMArena Text: legal and government13571451Qwen3.7 Plus
LMArena Text: business and finance13431435Qwen3.7 Plus
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
Design Arena: websites11941269Qwen3.7 Plus
Design Arena: UI components12081261Qwen3.7 Plus
Design Arena: game dev11351262Qwen3.7 Plus
Design Arena: data viz11231276Qwen3.7 Plus
Design Arena: 3D11211239Qwen3.7 Plus
Design Arena: all code categories11781269Qwen3.7 Plus
Design Arena: SVG10381208Qwen3.7 Plus
Design Arena: ASCII artNot measured1143Only Qwen3.7 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 FlashQwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench60.8%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)41.7%73.0%Qwen3.7 Plus
DTBenchNot measured84.0%Only Qwen3.7 Plus measured
LMCANot measured37.6%Only Qwen3.7 Plus measured
LMArena Text13511454Qwen3.7 Plus
LMArena Text: instruction following13271439Qwen3.7 Plus
LMArena Text: creative writing12961438Qwen3.7 Plus
LMArena VisionNot measured1278Only Qwen3.7 Plus measured
LMArena Text: English13731458Qwen3.7 Plus
LMArena Text: non-English13301445Qwen3.7 Plus
LMArena Text: Chinese14031509Qwen3.7 Plus
LMArena Text: German13361471Qwen3.7 Plus
LMArena Text: JapaneseNot measured1412Only Qwen3.7 Plus measured
LMArena Text: Korean12831413Qwen3.7 Plus
LMArena Text: French13321472Qwen3.7 Plus
LMArena Text: Spanish13501457Qwen3.7 Plus
LMArena Text: Russian13331457Qwen3.7 Plus
LMArena Text: Polish12911449Qwen3.7 Plus
LMArena Text: multi-turn13421459Qwen3.7 Plus
LMArena Text: longer queries13451454Qwen3.7 Plus
LMArena Text: writing and language13201437Qwen3.7 Plus
LMArena Text: entertainment and media13041422Qwen3.7 Plus
LMArena Vision: EnglishNot measured1280Only Qwen3.7 Plus measured
LMArena Vision: ChineseNot measured1332Only Qwen3.7 Plus measured
LMArena Vision: reading textNot measured1288Only Qwen3.7 Plus measured
LMArena Vision: humorNot measured1261Only Qwen3.7 Plus measured
LMArena Vision: creative writingNot measured1258Only Qwen3.7 Plus measured
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.7 Flash and Qwen3.7 Plus
BenchmarkGLM 4.7 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 4.7 Flash$0.0003Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

GLM 4.7 Flash$0.0045Fits in one request
Qwen3.7 Plus$0.020Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 4.7 Flash$0.017Exceeds the context window
Qwen3.7 Plus$0.077Fits in one request

GLM 4.7 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 4.7 Flash and Qwen3.7 Plus
SpecificationZ.ai GLM 4.7 FlashQwen3.7 Plus
MakerZ.aiQwen
WeightsOpen weightsNo public weights listed
ReleasedJanuary 19, 2026June 3, 2026
Context window200K1M
Input $/Mtok$0.0653$0.32
Output $/Mtok$0.40$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it02
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 3.2x cheaper ($0.40 vs $1.28 per million) and work measured by τ²-Bench Telecom, where it leads.

Which is cheaper, GLM 4.7 Flash or Qwen3.7 Plus?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.7 Flash or Qwen3.7 Plus?

Qwen3.7 Plus, with 1M tokens against 200K.

How many benchmarks is the GLM 4.7 Flash vs Qwen3.7 Plus comparison based on?

43 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 Flash's coding index rests on 0 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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