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Gemini 3.7 Flash vs GLM 5.3 Flash

Gemini 3.7 Flash leads GLM 5.3 Flash on coding, 58.0 to 57.7 on the Vibe Coding Index, and GLM 5.3 Flash costs 7.5x less per output token ($0.50 vs $3.75 per million). Updated October 22, 2026; 97 benchmarks have a result for both.

Replace Gemini 3.7 Flash Replace GLM 5.3 Flash
Gemini 3.7 FlashGoogle
Coding
58.0
Overall
65.7
Output $/M
$3.75
74
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
21
vs boards won of 97 shared, 2 tied

Gemini 3.7 Flash or GLM 5.3 Flash: which to pick

Gemini 3.7 Flash and GLM 5.3 Flash are level for coding, 58.0 against 57.7 on the Vibe Coding Index, so price and context decide.

Pick GLM 5.3 Flash for output tokens 7.5x cheaper ($0.50 vs $3.75 per million) and a lower cost per solved task ($0.02 against $1.78). Pick Gemini 3.7 Flash for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Model AGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved taskModel BGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved task
Shared results
97
Gemini 3.7 Flash only
17
GLM 5.3 Flash 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
Gemini 3.7 Flash 58.0 from 6 benchmarks, GLM 5.3 Flash 57.7 from 6 benchmarks.
Widest category
Math, 13.0 points apart on average over 6 shared benchmarks.
Widest single gap
Chess puzzles: Gemini 3.7 Flash 66.0% against GLM 5.3 Flash 21.0%, 45.0 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against GLM 5.3 Flash $0.50 per million output tokens, 7.5x apart.
Context window
Both take 1.05M tokens.

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
CategoryGemini 3.7 FlashBarsGLM 5.3 FlashTies
Coding1282 ties
Intelligence11
Agentic work64
Reasoning141
Math60
Knowledge61
Web design54
General242
All shared boards74212 ties
CodingLike-for-likeSix of these boards feed the Vibe Coding Index128
Coding benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
LiveBench coding80.5%80.6%GLM 5.3 Flash
LMArena WebDev15911607GLM 5.3 Flash
AA Coding Index71.571.5Tie
LiveCodeBench (Vals AI)88.7%80.5%Gemini 3.7 Flash
SWE-bench Verified (Vals AI)80.8%92.0%GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)12.1%37.4%GLM 5.3 Flash
Vibe Code Bench (Vals AI)70.4%30.8%Gemini 3.7 Flash
Code migration (Vals AI)34.8%20.5%Gemini 3.7 Flash
ProgramBench (Vals AI)0.0%0.0%Tie
IOI (Vals AI)67.8%52.5%Gemini 3.7 Flash
Terminal-Bench 2.1 (Vals AI)77.5%62.9%Gemini 3.7 Flash
Vibe Code Bench 1-100 (Vals AI)Not measured16.0%Only GLM 5.3 Flash measured
SkillsBench (Vals AI)65.9%40.2%Gemini 3.7 Flash
CyberBench (Vals AI)43.8%67.9%GLM 5.3 Flash
SciCode59.8%51.6%Gemini 3.7 Flash
FrontierCode43.6%31.8%Gemini 3.7 Flash
FrontierSWE20.3%18.1%Gemini 3.7 Flash
ALE-Bench904.3303.6Gemini 3.7 Flash
LMArena Text: coding14991507GLM 5.3 Flash
LMArena Text: software and IT14981500GLM 5.3 Flash
LMArena WebDev: React15871624GLM 5.3 Flash
LMArena WebDev: HTML15931577Gemini 3.7 Flash
LMArena WebDev: from an image15991578Gemini 3.7 Flash
SciCode13.8%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
AA Intelligence Index39.641.8GLM 5.3 Flash
Epoch Capabilities Index158.0153.1Gemini 3.7 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index64
Agentic work benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
AA Agentic IndexNot measured50.9Only GLM 5.3 Flash measured
Design Arena: agents building web apps1223Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building full-stack apps1208Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building mobile apps1229Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Android apps1243Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Godot games1264Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building games1235Not measuredOnly Gemini 3.7 Flash measured
Design Arena: spreadsheets1058Not measuredOnly Gemini 3.7 Flash measured
LiveBench research76.5%70.1%Gemini 3.7 Flash
LiveBench browser56.0%84.0%GLM 5.3 Flash
LiveBench long agentic28.3%28.4%GLM 5.3 Flash
SREBench (Vals AI)4.6%0.8%Gemini 3.7 Flash
Finance Agent (Vals AI)59.0%57.9%Gemini 3.7 Flash
Tax Agent Bench (Vals AI)22.8%31.6%GLM 5.3 Flash
Legal Research Bench (Vals AI)34.6%45.2%GLM 5.3 Flash
Harvey's Legal Agent Benchmark (Vals AI)Not measured10.4%Only GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)71.3%55.9%Gemini 3.7 Flash
Terminal-Bench-Science (Vals AI)7.1%2.9%Gemini 3.7 Flash
APEX-Agents67.8%52.8%Gemini 3.7 Flash
Remote Labor Index5.0%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index141
Reasoning benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
GPQA Diamond93.9%86.4%Gemini 3.7 Flash
LiveBench reasoning87.8%77.6%Gemini 3.7 Flash
MMMU Pro (Vals AI)89.0%86.0%Gemini 3.7 Flash
GPQA Diamond (Artificial Analysis run)94.5%91.2%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)47.9%39.9%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)94.8%90.2%Gemini 3.7 Flash
ARC-AGI95.5%91.0%Gemini 3.7 Flash
ARC-AGI-284.6%65.8%Gemini 3.7 Flash
Chess puzzles66.0%21.0%Gemini 3.7 Flash
Mystery game puzzles37.0%8.0%Gemini 3.7 Flash
LMArena Text: hard prompts14951490Gemini 3.7 Flash
LMArena Text: expert15121511Gemini 3.7 Flash
LMArena Text: hard prompts in English14871488GLM 5.3 Flash
LMArena Vision: diagrams13291317Gemini 3.7 Flash
LMArena Vision: homework13201318Gemini 3.7 Flash
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
OTIS Mock AIME97.2%93.9%Gemini 3.7 Flash
FrontierMath, tiers 1 to 371.6%55.8%Gemini 3.7 Flash
FrontierMath, tier 436.6%17.1%Gemini 3.7 Flash
ProofBench58.0%21.0%Gemini 3.7 Flash
LMArena Text: math15111503Gemini 3.7 Flash
LMArena Text: mathematical work15021497Gemini 3.7 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
Knowledge benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
MMLU Pro90.1%86.1%Gemini 3.7 Flash
LegalBench (Vals AI)87.3%83.9%Gemini 3.7 Flash
TaxEval (Vals AI)74.7%75.6%GLM 5.3 Flash
MortgageTax (Vals AI)66.7%Not measuredOnly Gemini 3.7 Flash measured
MedCode (Vals AI)53.4%Not measuredOnly Gemini 3.7 Flash measured
SimpleQA Verified69.2%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: science15111484Gemini 3.7 Flash
LMArena Text: medicine and healthcare14941475Gemini 3.7 Flash
LMArena Text: legal and government14961473Gemini 3.7 Flash
LMArena Text: business and finance14791460Gemini 3.7 Flash
FACTS Benchmark Suite71.2%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index54
Web design benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
Design Arena: websites13031272Gemini 3.7 Flash
Design Arena: UI components12961316GLM 5.3 Flash
Design Arena: game dev13171278Gemini 3.7 Flash
Design Arena: data viz13151262Gemini 3.7 Flash
Design Arena: 3D13071316GLM 5.3 Flash
Design Arena: all code categories13081282Gemini 3.7 Flash
Design Arena: SVG12831285GLM 5.3 Flash
Design Arena: ASCII art12761267Gemini 3.7 Flash
LiveBench design73.2%77.2%GLM 5.3 Flash
GeneralLike-for-likePublic boards, shown as published, kept out of the index242
General benchmarks for Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
Vals IndexNot measured50.9%Only GLM 5.3 Flash measured
LiveBench data analysis68.0%76.4%GLM 5.3 Flash
SAGE (Vals AI)49.2%Not measuredOnly Gemini 3.7 Flash measured
MedScribe (Vals AI)83.9%88.9%GLM 5.3 Flash
Long context reasoning (AA-LCR)83.0%80.0%Gemini 3.7 Flash
DTBench96.8%Not measuredOnly Gemini 3.7 Flash measured
LMCA50.4%Not measuredOnly Gemini 3.7 Flash measured
Surface Evolver BenchNot measured52.5%Only GLM 5.3 Flash measured
Furniture assembly26.7%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text14891471Gemini 3.7 Flash
LMArena Text: instruction following14841478Gemini 3.7 Flash
LMArena Text: creative writing14881441Gemini 3.7 Flash
LMArena Vision13141294Gemini 3.7 Flash
LMArena Text: English14831474Gemini 3.7 Flash
LMArena Text: non-English14871462Gemini 3.7 Flash
LMArena Text: Chinese15521531Gemini 3.7 Flash
LMArena Text: German15061462Gemini 3.7 Flash
LMArena Text: Japanese15111444Gemini 3.7 Flash
LMArena Text: Korean14811436Gemini 3.7 Flash
LMArena Text: French15001491Gemini 3.7 Flash
LMArena Text: Spanish14951475Gemini 3.7 Flash
LMArena Text: Russian15151465Gemini 3.7 Flash
LMArena Text: Polish15031450Gemini 3.7 Flash
LMArena Text: multi-turn14851469Gemini 3.7 Flash
LMArena Text: longer queries14921481Gemini 3.7 Flash
LMArena Text: writing and language14911455Gemini 3.7 Flash
LMArena Text: entertainment and media14771440Gemini 3.7 Flash
LMArena Vision: English13091295Gemini 3.7 Flash
LMArena Vision: Chinese13941363Gemini 3.7 Flash
LMArena Vision: reading text13221299Gemini 3.7 Flash
LMArena Vision: humor12991279Gemini 3.7 Flash
LMArena Vision: creative writing13121270Gemini 3.7 Flash
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 Gemini 3.7 Flash and GLM 5.3 Flash
BenchmarkGemini 3.7 FlashGLM 5.3 FlashLeader
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

Gemini 3.7 Flash$0.0026Fits in one request
GLM 5.3 Flash$0.0004Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request
GLM 5.3 Flash$0.0090Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request
GLM 5.3 Flash$0.035Fits 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 Gemini 3.7 Flash and GLM 5.3 Flash
SpecificationGoogle Gemini 3.7 FlashZ.ai GLM 5.3 Flash
MakerGoogleZ.ai
WeightsNo public weights listedOpen weights
ReleasedAugust 13, 2026August 26, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$0.15
Output $/Mtok$3.75$0.50
Coding index58.057.7
Independent measurements behind it66
Cost per solved task$1.78$0.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than GLM 5.3 Flash for coding?

Gemini 3.7 Flash and GLM 5.3 Flash are level for coding, 58.0 against 57.7 on the Vibe Coding Index, so price and context decide. Pick GLM 5.3 Flash for output tokens 7.5x cheaper ($0.50 vs $3.75 per million) and a lower cost per solved task ($0.02 against $1.78). Pick Gemini 3.7 Flash for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Which is cheaper, Gemini 3.7 Flash or GLM 5.3 Flash?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, Gemini 3.7 Flash costs $1.78 and GLM 5.3 Flash $0.02.

Which has the bigger context window, Gemini 3.7 Flash or GLM 5.3 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.7 Flash vs GLM 5.3 Flash comparison based on?

97 benchmarks have a result for both models as of October 22, 2026. Gemini 3.7 Flash's coding index rests on 6 independent benchmarks and GLM 5.3 Flash's on 6. 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/gemini-3-7-flash-vs-glm-5-3-flash">LLMBenchmark.ai, Gemini 3.7 Flash vs GLM 5.3 Flash</a></p>