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Gemini 2.5 Flash vs GLM 4.6

Updated October 21, 2026. 48 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 2.5 Flash Replace GLM 4.6
Gemini 2.5 FlashGoogle
Coding
28.7
Overall
15.5
Output $/M
$2.50
5
GLM 4.6Z.ai
Coding
52.2
Overall
18.5
Output $/M
$2.20
42
vs boards won of 48 shared, 1 tied

Decision reading

Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash.

Pick Gemini 2.5 Flash when the context window is larger, 1.05M against 205K tokens, or when what matters is GPQA Diamond (Artificial Analysis run) or MMLU Pro (Artificial Analysis run), where it leads.

Model AGemini 2.5 FlashGoogle28.7/1001 independent benchmark$0.466 per solved taskModel BGLM 4.6Z.ai52.2/1002 independent benchmarksNo cost per solved task
Shared results
48
Gemini 2.5 Flash only
21
GLM 4.6 only
18
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 2.5 Flash 28.7 from 1 benchmark, GLM 4.6 52.2 from 2 benchmarks.
Widest category
Agentic work, 45.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemini 2.5 Flash 31.6% against GLM 4.6 76.9%, 45.3 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash $2.50 against GLM 4.6 $2.20 per million output tokens, 1.1x apart.
Context window
Gemini 2.5 Flash takes 1.05M tokens, GLM 4.6 205K.

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 2.5 FlashBarsGLM 4.6Ties
Coding051 tie
Intelligence01
Agentic work01
Reasoning14
Math04
Knowledge14
Web design07
General316
All shared boards5421 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index05
Coding benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
SWE-bench Verified28.7%68.2%GLM 4.6
LMArena WebDevNot measured1341Only GLM 4.6 measured
AA Coding IndexNot measured45.8Only GLM 4.6 measured
LiveCodeBench (Vals AI)Not measured81.0%Only GLM 4.6 measured
Vibe Code Bench (Vals AI)Not measured3.1%Only GLM 4.6 measured
LiveCodeBench (Artificial Analysis run)69.5%69.5%Tie
Terminal-Bench Hard (Artificial Analysis run)13.6%28.8%GLM 4.6
Terminal-Bench17.1%24.5%GLM 4.6
ALE-BenchNot measured340.8Only GLM 4.6 measured
LMArena Text: coding14231449GLM 4.6
LMArena Text: software and IT14251455GLM 4.6
LMArena WebDev: HTMLNot measured1350Only GLM 4.6 measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
AA Intelligence Index15.518.5GLM 4.6
Epoch Capabilities Index142.9Not measuredOnly Gemini 2.5 Flash measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
Design Arena: agents building full-stack appsNot measured1029Only GLM 4.6 measured
Design Arena: agents building mobile appsNot measured1096Only GLM 4.6 measured
Design Arena: agents building Android appsNot measured1090Only GLM 4.6 measured
Design Arena: agents building Godot gamesNot measured1180Only GLM 4.6 measured
τ²-Bench Telecom31.6%76.9%GLM 4.6
BALROG33.5%Not measuredOnly Gemini 2.5 Flash measured
Vending-Bench 2$549Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
Reasoning benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
GPQA DiamondNot measured74.5%Only GLM 4.6 measured
GPQA Diamond (Artificial Analysis run)79.0%78.0%Gemini 2.5 Flash
Humanity's Last Exam (Artificial Analysis run)12.1%14.5%GLM 4.6
ARC-AGI33.3%Not measuredOnly Gemini 2.5 Flash measured
ARC-AGI-22.5%Not measuredOnly Gemini 2.5 Flash measured
SimpleBench41.2%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: hard prompts14221440GLM 4.6
LMArena Text: expert14261432GLM 4.6
LMArena Text: hard prompts in English14201445GLM 4.6
LMArena Vision: diagrams1245Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: homework1244Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
AIMENot measured92.7%Only GLM 4.6 measured
MGSM (Vals AI)Not measured89.8%Only GLM 4.6 measured
AA Math Index73.386.0GLM 4.6
AIME 2025 (Artificial Analysis run)73.3%86.0%GLM 4.6
LMArena Text: math14111432GLM 4.6
LMArena Text: mathematical work14221447GLM 4.6
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
MMLU ProNot measured82.2%Only GLM 4.6 measured
LegalBench (Vals AI)Not measured79.6%Only GLM 4.6 measured
CorpFin (Vals AI)Not measured56.8%Only GLM 4.6 measured
TaxEval (Vals AI)Not measured66.2%Only GLM 4.6 measured
MedQA (Vals AI)Not measured92.2%Only GLM 4.6 measured
MedCode (Vals AI)40.4%Not measuredOnly Gemini 2.5 Flash measured
MMLU Pro (Artificial Analysis run)83.2%82.9%Gemini 2.5 Flash
LMArena Text: science14331456GLM 4.6
LMArena Text: medicine and healthcare14281455GLM 4.6
LMArena Text: legal and government14301448GLM 4.6
LMArena Text: business and finance14041416GLM 4.6
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
Design Arena: websites10741174GLM 4.6
Design Arena: UI components10051147GLM 4.6
Design Arena: game dev10051151GLM 4.6
Design Arena: data viz10601161GLM 4.6
Design Arena: 3D10211129GLM 4.6
Design Arena: all code categories10591166GLM 4.6
Design Arena: SVG10181108GLM 4.6
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index316
General benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
SAGE (Vals AI)44.8%Not measuredOnly Gemini 2.5 Flash measured
MedScribe (Vals AI)83.0%Not measuredOnly Gemini 2.5 Flash measured
IFBench50.3%43.4%Gemini 2.5 Flash
Long context reasoning (AA-LCR)65.3%54.0%Gemini 2.5 Flash
DTBench76.5%Not measuredOnly Gemini 2.5 Flash measured
LMCA27.5%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text14171440GLM 4.6
LMArena Text: instruction following14051410GLM 4.6
LMArena Text: creative writing14001412GLM 4.6
LMArena Vision1235Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: English14181449GLM 4.6
LMArena Text: non-English14091426GLM 4.6
LMArena Text: Chinese14491499GLM 4.6
LMArena Text: German14171447GLM 4.6
LMArena Text: Japanese13961393Gemini 2.5 Flash
LMArena Text: Korean13851400GLM 4.6
LMArena Text: French14321459GLM 4.6
LMArena Text: Spanish14221436GLM 4.6
LMArena Text: Russian14151418GLM 4.6
LMArena Text: Polish14131447GLM 4.6
LMArena Text: multi-turn14081427GLM 4.6
LMArena Text: longer queries14191422GLM 4.6
LMArena Text: writing and language14051415GLM 4.6
LMArena Text: entertainment and media13931409GLM 4.6
LMArena Vision: English1239Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: Chinese1284Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: reading text1237Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: humor1225Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: captioning1277Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: recognizing things1252Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: creative writing1241Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Flash and GLM 4.6
BenchmarkGemini 2.5 FlashGLM 4.6Leader
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 2.5 Flash$0.0015Fits in one request
GLM 4.6$0.0016Fits in one request

Gemini 2.5 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash$0.022Fits in one request
GLM 4.6$0.034Fits in one request

Gemini 2.5 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash$0.085Fits in one request
GLM 4.6$0.132Exceeds the context window

Gemini 2.5 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 2.5 Flash and GLM 4.6
SpecificationGoogle Gemini 2.5 FlashZ.ai GLM 4.6
MakerGoogleZ.ai
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025September 30, 2025
Context window1.05M205K
Input $/Mtok$0.30$0.55
Output $/Mtok$2.50$2.20
Coding index28.752.2
Independent measurements behind it12
Cost per solved task$0.466Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash better than GLM 4.6 for coding?

Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash. Pick Gemini 2.5 Flash when the context window is larger, 1.05M against 205K tokens, or when what matters is GPQA Diamond (Artificial Analysis run) or MMLU Pro (Artificial Analysis run), where it leads.

Which is cheaper, Gemini 2.5 Flash or GLM 4.6?

Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; GLM 4.6 costs $0.55 and $2.20. Cost per solved task is known for Gemini 2.5 Flash only.

Which has the bigger context window, Gemini 2.5 Flash or GLM 4.6?

Gemini 2.5 Flash, with 1.05M tokens against 205K.

How many benchmarks is the Gemini 2.5 Flash vs GLM 4.6 comparison based on?

48 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash's coding index rests on 1 independent benchmark and GLM 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.

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