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Gemini 3.5 Flash vs GLM 4.7 Flash

Updated October 21, 2026. 43 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 3.5 Flash Replace GLM 4.7 Flash
Gemini 3.5 FlashGoogle
Coding
39.8
Overall
33.6
Output $/M
$9.00
42
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
1
vs boards won of 43 shared

Decision reading

Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.

GLM 4.7 Flash has the edge where output tokens cost 22.5x less, and where the benchmark that matters is τ²-Bench Telecom, where it leads.

Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
43
Gemini 3.5 Flash only
67
GLM 4.7 Flash only
0
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 4.7 Flash not benchmarked.
Widest category
Math, 27.6 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Text: Polish: Gemini 3.5 Flash 1516 against GLM 4.7 Flash 1291, 37.6 points apart on a 0 to 100 scale.
Output price
Gemini 3.5 Flash $9.00 against GLM 4.7 Flash $0.40 per million output tokens, 22.5x apart.
Context window
Gemini 3.5 Flash takes 1.05M tokens, GLM 4.7 Flash 200K.

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 4.7 FlashTies
Coding30
Intelligence10
Agentic work01
Reasoning60
Math30
Knowledge40
Web design70
General180
All shared boards421
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
LMArena WebDev1499Not measuredOnly Gemini 3.5 Flash measured
LiveCodeBench (Vals AI)87.6%Not measuredOnly Gemini 3.5 Flash measured
SWE-bench Verified (Vals AI)78.8%Not measuredOnly Gemini 3.5 Flash measured
Terminal-Bench 4 (Vals AI)6.1%Not measuredOnly Gemini 3.5 Flash measured
Vibe Code Bench (Vals AI)48.7%Not measuredOnly Gemini 3.5 Flash measured
Code migration (Vals AI)26.8%Not measuredOnly Gemini 3.5 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.5 Flash measured
Terminal-Bench 2.1 (Vals AI)74.2%Not measuredOnly Gemini 3.5 Flash measured
SkillsBench (Vals AI)52.7%Not measuredOnly Gemini 3.5 Flash measured
SciCode53.9%Not measuredOnly Gemini 3.5 Flash measured
Terminal-Bench Hard (Artificial Analysis run)46.2%22.0%Gemini 3.5 Flash
WeirdML62.6%Not measuredOnly Gemini 3.5 Flash measured
ALE-Bench911.0Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: coding14931382Gemini 3.5 Flash
LMArena Text: software and IT14941389Gemini 3.5 Flash
LMArena WebDev: React1495Not measuredOnly Gemini 3.5 Flash measured
LMArena WebDev: HTML1522Not measuredOnly Gemini 3.5 Flash measured
LMArena WebDev: from an image1504Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
AA Intelligence Index33.614.9Gemini 3.5 Flash
Epoch Capabilities Index154.9Not measuredOnly Gemini 3.5 Flash measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
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 apps1175Not measuredOnly Gemini 3.5 Flash measured
Design Arena: agents building Android apps1190Not 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 slides1142Not measuredOnly Gemini 3.5 Flash measured
Design Arena: PowerPoint slides1179Not measuredOnly Gemini 3.5 Flash measured
Finance Agent (Vals AI)57.9%Not measuredOnly Gemini 3.5 Flash measured
Tax Agent Bench (Vals AI)21.6%Not measuredOnly Gemini 3.5 Flash measured
Legal Research Bench (Vals AI)30.8%Not measuredOnly Gemini 3.5 Flash measured
Excel Modeling Benchmark (Vals AI)63.5%Not measuredOnly Gemini 3.5 Flash measured
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly Gemini 3.5 Flash measured
τ²-Bench Telecom95.6%98.8%GLM 4.7 Flash
APEX-Agents27.5%Not measuredOnly Gemini 3.5 Flash measured
Vending-Bench 2$5,396Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
GPQA Diamond92.7%Not measuredOnly Gemini 3.5 Flash measured
MMMU Pro (Vals AI)88.3%Not measuredOnly Gemini 3.5 Flash measured
GPQA Diamond (Artificial Analysis run)92.2%58.1%Gemini 3.5 Flash
Humanity's Last Exam (Artificial Analysis run)42.7%7.6%Gemini 3.5 Flash
GPQA Diamond (Epoch AI run)92.8%60.5%Gemini 3.5 Flash
ARC-AGI92.5%Not measuredOnly Gemini 3.5 Flash measured
ARC-AGI-272.1%Not measuredOnly Gemini 3.5 Flash measured
SimpleBench76.7%Not measuredOnly Gemini 3.5 Flash measured
Chess puzzles45.0%Not measuredOnly Gemini 3.5 Flash measured
Mystery game puzzles32.0%Not measuredOnly Gemini 3.5 Flash measured
EBR-bench4.8%Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: hard prompts14881356Gemini 3.5 Flash
LMArena Text: expert14951357Gemini 3.5 Flash
LMArena Text: hard prompts in English14831369Gemini 3.5 Flash
LMArena Vision: diagrams1323Not measuredOnly Gemini 3.5 Flash measured
LMArena Vision: homework1330Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
OTIS Mock AIME95.6%58.3%Gemini 3.5 Flash
FrontierMath, tiers 1 to 362.8%Not measuredOnly Gemini 3.5 Flash measured
FrontierMath, tier 426.8%Not measuredOnly Gemini 3.5 Flash measured
ProofBench31.0%Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: math15041355Gemini 3.5 Flash
LMArena Text: mathematical work14951369Gemini 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 index40
Knowledge benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
MMLU Pro89.5%Not measuredOnly Gemini 3.5 Flash measured
LegalBench (Vals AI)83.6%Not measuredOnly Gemini 3.5 Flash measured
CorpFin (Vals AI)64.7%Not measuredOnly Gemini 3.5 Flash measured
TaxEval (Vals AI)74.4%Not measuredOnly Gemini 3.5 Flash measured
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: science14951358Gemini 3.5 Flash
LMArena Text: medicine and healthcare14831343Gemini 3.5 Flash
LMArena Text: legal and government14881357Gemini 3.5 Flash
LMArena Text: business and finance14671343Gemini 3.5 Flash
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
Design Arena: websites12681194Gemini 3.5 Flash
Design Arena: UI components12731208Gemini 3.5 Flash
Design Arena: game dev12631135Gemini 3.5 Flash
Design Arena: data viz12361123Gemini 3.5 Flash
Design Arena: 3D12441121Gemini 3.5 Flash
Design Arena: all code categories12661178Gemini 3.5 Flash
Design Arena: SVG12541038Gemini 3.5 Flash
Design Arena: ASCII art1254Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for Gemini 3.5 Flash and GLM 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 FlashLeader
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%Not measuredOnly Gemini 3.5 Flash measured
Vals Multimodal Index62.9%Not measuredOnly Gemini 3.5 Flash measured
IFBench76.3%60.8%Gemini 3.5 Flash
Long context reasoning (AA-LCR)74.3%41.7%Gemini 3.5 Flash
DTBench94.7%Not measuredOnly Gemini 3.5 Flash measured
LMCA47.1%Not measuredOnly Gemini 3.5 Flash measured
Surface Evolver Bench58.1%Not measuredOnly Gemini 3.5 Flash measured
LMArena Text14821351Gemini 3.5 Flash
LMArena Text: instruction following14671327Gemini 3.5 Flash
LMArena Text: creative writing14701296Gemini 3.5 Flash
LMArena Vision1308Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: English14811373Gemini 3.5 Flash
LMArena Text: non-English14751330Gemini 3.5 Flash
LMArena Text: Chinese15271403Gemini 3.5 Flash
LMArena Text: German14941336Gemini 3.5 Flash
LMArena Text: Japanese1486Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: Korean14481283Gemini 3.5 Flash
LMArena Text: French14901332Gemini 3.5 Flash
LMArena Text: Spanish14801350Gemini 3.5 Flash
LMArena Text: Russian14931333Gemini 3.5 Flash
LMArena Text: Polish15161291Gemini 3.5 Flash
LMArena Text: multi-turn14811342Gemini 3.5 Flash
LMArena Text: longer queries14831345Gemini 3.5 Flash
LMArena Text: writing and language14781320Gemini 3.5 Flash
LMArena Text: entertainment and media14591304Gemini 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 4.7 Flash
BenchmarkGemini 3.5 FlashGLM 4.7 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 4.7 Flash$0.0003Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.5 Flash$0.102Fits in one request
GLM 4.7 Flash$0.0045Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.5 Flash$0.390Fits in one request
GLM 4.7 Flash$0.017Exceeds the context window

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 Gemini 3.5 Flash and GLM 4.7 Flash
SpecificationGoogle Gemini 3.5 FlashZ.ai GLM 4.7 Flash
MakerGoogleZ.ai
WeightsNo public weights listedOpen weights
ReleasedMay 19, 2026January 19, 2026
Context window1.05M200K
Input $/Mtok$1.50$0.0653
Output $/Mtok$9.00$0.40
Coding index39.8Not benchmarked
Independent measurements behind it40
Cost per solved task$1.21Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.5 Flash better than GLM 4.7 Flash for coding?

Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. GLM 4.7 Flash has the edge where output tokens cost 22.5x less, and where the benchmark that matters is τ²-Bench Telecom, where it leads.

Which is cheaper, Gemini 3.5 Flash or GLM 4.7 Flash?

Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for Gemini 3.5 Flash only.

Which has the bigger context window, Gemini 3.5 Flash or GLM 4.7 Flash?

Gemini 3.5 Flash, with 1.05M tokens against 200K.

How many benchmarks is the Gemini 3.5 Flash vs GLM 4.7 Flash comparison based on?

43 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 4.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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