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Gemini 3.5 Flash vs GLM 5.3 Flash

GLM 5.3 Flash leads Gemini 3.5 Flash on coding, 57.7 to 39.8 on the Vibe Coding Index, and GLM 5.3 Flash costs 18.0x less per output token ($0.50 vs $9.00 per million). Updated October 22, 2026; 85 benchmarks have a result for both.

Replace Gemini 3.5 Flash Replace GLM 5.3 Flash
Gemini 3.5 FlashGoogle
Coding
39.8
Overall
63.8
Output $/M
$9.00
53
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
31
vs boards won of 85 shared, 1 tied

Gemini 3.5 Flash or GLM 5.3 Flash: which to pick

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash.

Pick Gemini 3.5 Flash for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved task
Shared results
85
Gemini 3.5 Flash only
27
GLM 5.3 Flash only
17
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 3.5 Flash 39.8 from 4 benchmarks, GLM 5.3 Flash 57.7 from 6 benchmarks.
Widest category
Coding, 11.9 points apart on average over 16 shared benchmarks.
Widest single gap
Terminal-Bench 4 (Vals AI): Gemini 3.5 Flash 6.1% against GLM 5.3 Flash 37.4%, 41.7 points apart on a 0 to 100 scale.
Output price
Gemini 3.5 Flash $9.00 against GLM 5.3 Flash $0.50 per million output tokens, 18.0x 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 3.5 FlashBarsGLM 5.3 FlashTies
Coding781 tie
Intelligence11
Agentic work33
Reasoning113
Math51
Knowledge52
Web design08
General215
All shared boards53311 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index78
Coding benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
LiveBench codingNot measured80.6%Only GLM 5.3 Flash measured
LMArena WebDev14991607GLM 5.3 Flash
AA Coding IndexNot measured71.5Only GLM 5.3 Flash measured
LiveCodeBench (Vals AI)87.6%80.5%Gemini 3.5 Flash
SWE-bench Verified (Vals AI)78.8%92.0%GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)6.1%37.4%GLM 5.3 Flash
Vibe Code Bench (Vals AI)48.7%30.8%Gemini 3.5 Flash
Code migration (Vals AI)26.8%20.5%Gemini 3.5 Flash
ProgramBench (Vals AI)0.0%0.0%Tie
IOI (Vals AI)Not measured52.5%Only GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)74.2%62.9%Gemini 3.5 Flash
Vibe Code Bench 1-100 (Vals AI)Not measured16.0%Only GLM 5.3 Flash measured
SkillsBench (Vals AI)52.7%40.2%Gemini 3.5 Flash
CyberBench (Vals AI)Not measured67.9%Only GLM 5.3 Flash measured
SciCode53.9%51.6%Gemini 3.5 Flash
Terminal-Bench Hard (Artificial Analysis run)46.2%Not measuredOnly Gemini 3.5 Flash measured
FrontierCodeNot measured31.8%Only GLM 5.3 Flash measured
FrontierSWENot measured18.1%Only GLM 5.3 Flash measured
WeirdML62.6%Not measuredOnly Gemini 3.5 Flash measured
ALE-Bench911.0303.6Gemini 3.5 Flash
LMArena Text: coding14931507GLM 5.3 Flash
LMArena Text: software and IT14941500GLM 5.3 Flash
LMArena WebDev: React14951624GLM 5.3 Flash
LMArena WebDev: HTML15221577GLM 5.3 Flash
LMArena WebDev: from an image15041578GLM 5.3 Flash
SciCode12.3%Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
AA Intelligence Index33.641.8GLM 5.3 Flash
Epoch Capabilities Index154.9153.1Gemini 3.5 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index33
Agentic work benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
AA Agentic IndexNot measured50.9Only GLM 5.3 Flash measured
Design Arena: agents building web apps1202Not measuredOnly Gemini 3.5 Flash measured
Design Arena: agents building full-stack apps1197Not measuredOnly Gemini 3.5 Flash measured
Design Arena: agents building mobile apps1174Not measuredOnly Gemini 3.5 Flash measured
Design Arena: agents building Android apps1185Not measuredOnly Gemini 3.5 Flash measured
Design Arena: agents building Godot games1098Not measuredOnly Gemini 3.5 Flash measured
Design Arena: agents building games1180Not measuredOnly Gemini 3.5 Flash measured
Design Arena: HTML slides1093Not measuredOnly Gemini 3.5 Flash measured
Design Arena: PowerPoint slides1154Not measuredOnly Gemini 3.5 Flash measured
LiveBench researchNot measured70.1%Only GLM 5.3 Flash measured
LiveBench browserNot measured84.0%Only GLM 5.3 Flash measured
LiveBench long agenticNot measured28.4%Only GLM 5.3 Flash measured
SREBench (Vals AI)Not measured0.8%Only GLM 5.3 Flash measured
Finance Agent (Vals AI)57.9%57.9%Gemini 3.5 Flash
Tax Agent Bench (Vals AI)21.6%31.6%GLM 5.3 Flash
Legal Research Bench (Vals AI)30.8%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)63.5%55.9%Gemini 3.5 Flash
Terminal-Bench-Science (Vals AI)5.7%2.9%Gemini 3.5 Flash
τ²-Bench Telecom95.6%Not measuredOnly Gemini 3.5 Flash measured
APEX-Agents27.5%52.8%GLM 5.3 Flash
Vending-Bench 2$5,396Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 19 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index113
Reasoning benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
GPQA Diamond92.7%86.4%Gemini 3.5 Flash
LiveBench reasoningNot measured77.6%Only GLM 5.3 Flash measured
MMMU Pro (Vals AI)88.3%86.0%Gemini 3.5 Flash
GPQA Diamond (Artificial Analysis run)92.2%91.2%Gemini 3.5 Flash
Humanity's Last Exam (Artificial Analysis run)42.7%39.9%Gemini 3.5 Flash
GPQA Diamond (Epoch AI run)92.8%90.2%Gemini 3.5 Flash
ARC-AGI92.5%91.0%Gemini 3.5 Flash
ARC-AGI-272.1%65.8%Gemini 3.5 Flash
SimpleBench76.7%Not measuredOnly Gemini 3.5 Flash measured
Chess puzzles45.0%21.0%Gemini 3.5 Flash
Mystery game puzzles32.0%8.0%Gemini 3.5 Flash
EBR-bench4.8%Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: hard prompts14881490GLM 5.3 Flash
LMArena Text: expert14951511GLM 5.3 Flash
LMArena Text: hard prompts in English14831488GLM 5.3 Flash
LMArena Vision: diagrams13231317Gemini 3.5 Flash
LMArena Vision: homework13301318Gemini 3.5 Flash
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index51
Math benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
OTIS Mock AIME95.6%93.9%Gemini 3.5 Flash
FrontierMath, tiers 1 to 362.8%55.8%Gemini 3.5 Flash
FrontierMath, tier 426.8%17.1%Gemini 3.5 Flash
ProofBench31.0%21.0%Gemini 3.5 Flash
LMArena Text: math15041503Gemini 3.5 Flash
LMArena Text: mathematical work14951497GLM 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 index52
Knowledge benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
MMLU Pro89.5%86.1%Gemini 3.5 Flash
LegalBench (Vals AI)83.6%83.9%GLM 5.3 Flash
CorpFin (Vals AI)64.7%Not measuredOnly Gemini 3.5 Flash measured
TaxEval (Vals AI)74.4%75.6%GLM 5.3 Flash
MortgageTax (Vals AI)68.1%Not measuredOnly Gemini 3.5 Flash measured
MedCode (Vals AI)55.8%Not measuredOnly Gemini 3.5 Flash measured
SimpleQA Verified66.2%Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: science14951484Gemini 3.5 Flash
LMArena Text: medicine and healthcare14831475Gemini 3.5 Flash
LMArena Text: legal and government14881473Gemini 3.5 Flash
LMArena Text: business and finance14671460Gemini 3.5 Flash
FACTS Benchmark Suite63.1%Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
Design Arena: websites12671272GLM 5.3 Flash
Design Arena: UI components12691316GLM 5.3 Flash
Design Arena: game dev12631278GLM 5.3 Flash
Design Arena: data viz12361262GLM 5.3 Flash
Design Arena: 3D12431316GLM 5.3 Flash
Design Arena: all code categories12661282GLM 5.3 Flash
Design Arena: SVG12531285GLM 5.3 Flash
Design Arena: ASCII art12541267GLM 5.3 Flash
LiveBench designNot measured77.2%Only GLM 5.3 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index215
General benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 FlashGLM 5.3 FlashLeader
Vals IndexNot measured50.9%Only GLM 5.3 Flash measured
LiveBench data analysisNot measured76.4%Only GLM 5.3 Flash measured
Public Benefits Bench (Vals AI)59.5%Not measuredOnly Gemini 3.5 Flash measured
SAGE (Vals AI)49.9%Not measuredOnly Gemini 3.5 Flash measured
MedScribe (Vals AI)76.6%88.9%GLM 5.3 Flash
Vals Multimodal Index62.9%Not measuredOnly Gemini 3.5 Flash measured
IFBench76.3%Not measuredOnly Gemini 3.5 Flash measured
Long context reasoning (AA-LCR)74.3%80.0%GLM 5.3 Flash
DTBench94.7%Not measuredOnly Gemini 3.5 Flash measured
LMCA47.1%Not measuredOnly Gemini 3.5 Flash measured
Surface Evolver Bench58.1%52.5%Gemini 3.5 Flash
LMArena Text14821471Gemini 3.5 Flash
LMArena Text: instruction following14671478GLM 5.3 Flash
LMArena Text: creative writing14701441Gemini 3.5 Flash
LMArena Vision13081294Gemini 3.5 Flash
LMArena Text: English14811474Gemini 3.5 Flash
LMArena Text: non-English14751462Gemini 3.5 Flash
LMArena Text: Chinese15271531GLM 5.3 Flash
LMArena Text: German14941462Gemini 3.5 Flash
LMArena Text: Japanese14861444Gemini 3.5 Flash
LMArena Text: Korean14481436Gemini 3.5 Flash
LMArena Text: French14901491GLM 5.3 Flash
LMArena Text: Spanish14801475Gemini 3.5 Flash
LMArena Text: Russian14931465Gemini 3.5 Flash
LMArena Text: Polish15161450Gemini 3.5 Flash
LMArena Text: multi-turn14811469Gemini 3.5 Flash
LMArena Text: longer queries14831481Gemini 3.5 Flash
LMArena Text: writing and language14781455Gemini 3.5 Flash
LMArena Text: entertainment and media14591440Gemini 3.5 Flash
LMArena Vision: English13051295Gemini 3.5 Flash
LMArena Vision: Chinese13771363Gemini 3.5 Flash
LMArena Vision: reading text13171299Gemini 3.5 Flash
LMArena Vision: humor13211279Gemini 3.5 Flash
LMArena Vision: creative writing13011270Gemini 3.5 Flash
LMArena Document1463Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.5 Flash and GLM 5.3 Flash
BenchmarkGemini 3.5 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 3.5 Flash$0.0060Fits 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 3.5 Flash$0.102Fits 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 3.5 Flash$0.390Fits 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 3.5 Flash and GLM 5.3 Flash
SpecificationGoogle Gemini 3.5 FlashZ.ai GLM 5.3 Flash
MakerGoogleZ.ai
WeightsNo public weights listedOpen weights
ReleasedMay 19, 2026August 26, 2026
Context window1.05M1.05M
Input $/Mtok$1.50$0.15
Output $/Mtok$9.00$0.50
Coding index39.857.7
Independent measurements behind it46
Cost per solved task$1.21$0.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.5 Flash better than GLM 5.3 Flash for coding?

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash. Pick Gemini 3.5 Flash for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Which is cheaper, Gemini 3.5 Flash or GLM 5.3 Flash?

Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, Gemini 3.5 Flash costs $1.21 and GLM 5.3 Flash $0.02.

Which has the bigger context window, Gemini 3.5 Flash or GLM 5.3 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.5 Flash vs GLM 5.3 Flash comparison based on?

85 benchmarks have a result for both models as of October 22, 2026. Gemini 3.5 Flash's coding index rests on 4 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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