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Gemini 3.5 Flash vs GLM 5.2

GLM 5.2 leads Gemini 3.5 Flash on coding, 61.1 to 39.8 on the Vibe Coding Index, and GLM 5.2 costs 2.0x less per output token ($4.40 vs $9.00 per million). Updated October 21, 2026; 92 benchmarks have a result for both.

Replace Gemini 3.5 Flash Replace GLM 5.2
Gemini 3.5 FlashGoogle
Coding
39.8
Overall
63.8
Output $/M
$9.00
58
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
34
vs boards won of 92 shared

Gemini 3.5 Flash or GLM 5.2: which to pick

Pick GLM 5.2 for coding: it scores 61.1 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 Terminal-Bench 2.1 (Vals AI), where it leads.

Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved task
Shared results
92
Gemini 3.5 Flash only
20
GLM 5.2 only
6
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 5.2 61.1 from 4 benchmarks.
Widest category
Reasoning, 10.7 points apart on average over 13 shared benchmarks.
Widest single gap
ARC-AGI-2: Gemini 3.5 Flash 72.1% against GLM 5.2 22.8%, 49.3 points apart on a 0 to 100 scale.
Output price
Gemini 3.5 Flash $9.00 against GLM 5.2 $4.40 per million output tokens, 2.0x 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 5.2Ties
Coding610
Intelligence11
Agentic work410
Reasoning121
Math42
Knowledge82
Web design26
General212
All shared boards5834
CodingLike-for-likeSix of these boards feed the Vibe Coding Index610
Coding benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
LMArena WebDev14991604GLM 5.2
AA Coding IndexNot measured68.8Only GLM 5.2 measured
LiveCodeBench (Vals AI)87.6%69.5%Gemini 3.5 Flash
SWE-bench Verified (Vals AI)78.8%82.8%GLM 5.2
Terminal-Bench 4 (Vals AI)6.1%Not measuredOnly Gemini 3.5 Flash measured
Vibe Code Bench (Vals AI)48.7%64.0%GLM 5.2
Code migration (Vals AI)26.8%37.9%GLM 5.2
ProgramBench (Vals AI)0.0%0.5%GLM 5.2
Terminal-Bench 2.1 (Vals AI)74.2%67.8%Gemini 3.5 Flash
SkillsBench (Vals AI)52.7%45.1%Gemini 3.5 Flash
SciCode53.9%51.2%Gemini 3.5 Flash
Terminal-Bench Hard (Artificial Analysis run)46.2%50.8%GLM 5.2
FrontierCodeNot measured24.5%Only GLM 5.2 measured
WeirdML62.6%70.1%GLM 5.2
ALE-Bench911.01047.0GLM 5.2
LMArena Text: coding14931487Gemini 3.5 Flash
LMArena Text: software and IT14941486Gemini 3.5 Flash
LMArena WebDev: React14951617GLM 5.2
LMArena WebDev: HTML15221565GLM 5.2
LMArena WebDev: from an image1504Not measuredOnly Gemini 3.5 Flash measured
SciCode12.3%Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
AA Intelligence Index33.633.7GLM 5.2
Epoch Capabilities Index154.9151.9Gemini 3.5 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index410
Agentic work benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
AA Agentic IndexNot measured38.4Only GLM 5.2 measured
Design Arena: agents building web apps12021222GLM 5.2
Design Arena: agents building full-stack apps11971241GLM 5.2
Design Arena: agents building mobile apps11741160Gemini 3.5 Flash
Design Arena: agents building Android apps11841178Gemini 3.5 Flash
Design Arena: agents building Godot games10981142GLM 5.2
Design Arena: agents building games11801206GLM 5.2
Design Arena: HTML slides11421175GLM 5.2
Design Arena: PowerPoint slides11791195GLM 5.2
SREBench (Vals AI)Not measured0.0%Only GLM 5.2 measured
Finance Agent (Vals AI)57.9%49.7%Gemini 3.5 Flash
Tax Agent Bench (Vals AI)21.6%Not measuredOnly Gemini 3.5 Flash measured
Legal Research Bench (Vals AI)30.8%31.3%GLM 5.2
Excel Modeling Benchmark (Vals AI)63.5%61.5%Gemini 3.5 Flash
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly Gemini 3.5 Flash measured
τ²-Bench Telecom95.6%99.1%GLM 5.2
APEX-Agents27.5%45.2%GLM 5.2
PostTrainBenchNot measured31.7%Only GLM 5.2 measured
Vending-Bench 2$5,396$8,314GLM 5.2
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index121
Reasoning benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
GPQA Diamond92.7%85.6%Gemini 3.5 Flash
MMMU Pro (Vals AI)88.3%Not measuredOnly Gemini 3.5 Flash measured
GPQA Diamond (Artificial Analysis run)92.2%89.5%Gemini 3.5 Flash
Humanity's Last Exam (Artificial Analysis run)42.7%41.1%Gemini 3.5 Flash
GPQA Diamond (Epoch AI run)92.8%91.9%Gemini 3.5 Flash
ARC-AGI92.5%77.0%Gemini 3.5 Flash
ARC-AGI-272.1%22.8%Gemini 3.5 Flash
SimpleBench76.7%58.8%Gemini 3.5 Flash
Chess puzzles45.0%22.0%Gemini 3.5 Flash
Mystery game puzzles32.0%19.0%Gemini 3.5 Flash
EBR-bench4.8%9.5%GLM 5.2
LMArena Text: hard prompts14881481Gemini 3.5 Flash
LMArena Text: expert14951487Gemini 3.5 Flash
LMArena Text: hard prompts in English14831481Gemini 3.5 Flash
LMArena Vision: diagrams1323Not measuredOnly Gemini 3.5 Flash measured
LMArena Vision: homework1330Not measuredOnly Gemini 3.5 Flash measured
Kagi LLM BenchmarkNot measured62.6%Only GLM 5.2 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index42
Math benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
OTIS Mock AIME95.6%86.4%Gemini 3.5 Flash
FrontierMath, tiers 1 to 362.8%59.2%Gemini 3.5 Flash
FrontierMath, tier 426.8%29.3%GLM 5.2
ProofBench31.0%35.0%GLM 5.2
LMArena Text: math15041483Gemini 3.5 Flash
LMArena Text: mathematical work14951489Gemini 3.5 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index82
Knowledge benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
MMLU Pro89.5%86.7%Gemini 3.5 Flash
LegalBench (Vals AI)83.6%84.1%GLM 5.2
CorpFin (Vals AI)64.7%66.1%GLM 5.2
TaxEval (Vals AI)74.4%73.3%Gemini 3.5 Flash
MortgageTax (Vals AI)68.1%Not measuredOnly Gemini 3.5 Flash measured
MedCode (Vals AI)55.8%40.8%Gemini 3.5 Flash
SimpleQA Verified66.2%34.2%Gemini 3.5 Flash
LMArena Text: science14951489Gemini 3.5 Flash
LMArena Text: medicine and healthcare14831475Gemini 3.5 Flash
LMArena Text: legal and government14881486Gemini 3.5 Flash
LMArena Text: business and finance14671451Gemini 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 index26
Web design benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
Design Arena: websites12681285GLM 5.2
Design Arena: UI components12731296GLM 5.2
Design Arena: game dev12631268GLM 5.2
Design Arena: data viz12361285GLM 5.2
Design Arena: 3D12441288GLM 5.2
Design Arena: all code categories12661288GLM 5.2
Design Arena: SVG12541214Gemini 3.5 Flash
Design Arena: ASCII art12541190Gemini 3.5 Flash
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index212
General benchmarks for Gemini 3.5 Flash and GLM 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
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%83.5%GLM 5.2
Vals Multimodal Index62.9%Not measuredOnly Gemini 3.5 Flash measured
IFBench76.3%73.3%Gemini 3.5 Flash
Long context reasoning (AA-LCR)74.3%78.3%GLM 5.2
DTBench94.7%93.6%Gemini 3.5 Flash
LMCA47.1%45.8%Gemini 3.5 Flash
Surface Evolver Bench58.1%55.6%Gemini 3.5 Flash
LMArena Text14821470Gemini 3.5 Flash
LMArena Text: instruction following14671466Gemini 3.5 Flash
LMArena Text: creative writing14701463Gemini 3.5 Flash
LMArena Vision1308Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: English14811475Gemini 3.5 Flash
LMArena Text: non-English14751459Gemini 3.5 Flash
LMArena Text: Chinese15271522Gemini 3.5 Flash
LMArena Text: German14941470Gemini 3.5 Flash
LMArena Text: Japanese14861450Gemini 3.5 Flash
LMArena Text: Korean14481440Gemini 3.5 Flash
LMArena Text: French14901479Gemini 3.5 Flash
LMArena Text: Spanish14801478Gemini 3.5 Flash
LMArena Text: Russian14931468Gemini 3.5 Flash
LMArena Text: Polish15161456Gemini 3.5 Flash
LMArena Text: multi-turn14811469Gemini 3.5 Flash
LMArena Text: longer queries14831480Gemini 3.5 Flash
LMArena Text: writing and language14781463Gemini 3.5 Flash
LMArena Text: entertainment and media14591450Gemini 3.5 Flash
LMArena Vision: English1305Not measuredOnly Gemini 3.5 Flash measured
LMArena Vision: Chinese1377Not measuredOnly Gemini 3.5 Flash measured
LMArena Vision: reading text1317Not measuredOnly Gemini 3.5 Flash measured
LMArena Vision: humor1321Not measuredOnly Gemini 3.5 Flash measured
LMArena Vision: creative writing1301Not measuredOnly Gemini 3.5 Flash measured
LMArena Document1463Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 13 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 5.2
BenchmarkGemini 3.5 FlashGLM 5.2Leader
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 5.2$0.0036Fits in one request

GLM 5.2 costs less

Repository review

50K input + 3K output tokens

Gemini 3.5 Flash$0.102Fits in one request
GLM 5.2$0.083Fits in one request

GLM 5.2 costs less

Agent loop

200K input + 10K output tokens

Gemini 3.5 Flash$0.390Fits in one request
GLM 5.2$0.324Fits in one request

GLM 5.2 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 5.2
SpecificationGoogle Gemini 3.5 FlashZ.ai GLM 5.2
MakerGoogleZ.ai
WeightsNo public weights listedOpen weights
ReleasedMay 19, 2026June 16, 2026
Context window1.05M1.05M
Input $/Mtok$1.50$1.40
Output $/Mtok$9.00$4.40
Coding index39.861.1
Independent measurements behind it44
Cost per solved task$1.21$0.86
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.5 Flash better than GLM 5.2 for coding?

Pick GLM 5.2 for coding: it scores 61.1 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 Terminal-Bench 2.1 (Vals AI), where it leads.

Which is cheaper, Gemini 3.5 Flash or GLM 5.2?

Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; GLM 5.2 costs $1.40 and $4.40. Per solved SWE-bench Verified task, Gemini 3.5 Flash costs $1.21 and GLM 5.2 $0.86.

Which has the bigger context window, Gemini 3.5 Flash or GLM 5.2?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.5 Flash vs GLM 5.2 comparison based on?

92 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash's coding index rests on 4 independent benchmarks and GLM 5.2's on 4. Where only one model has a result, the page says so instead of naming a winner.

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