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Gemini 2.5 Pro vs GLM 4.6

Updated October 21, 2026. 52 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 Pro Replace GLM 4.6
Gemini 2.5 ProGoogle
Coding
37.0
Overall
16.1
Output $/M
$10.00
39
GLM 4.6Z.ai
Coding
52.2
Overall
18.5
Output $/M
$2.20
13
vs boards won of 52 shared

Decision reading

Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro.

Pick Gemini 2.5 Pro when the context window is larger, 1.05M against 205K tokens, or when what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench, where it leads.

Model AGemini 2.5 ProGoogle37.0/1002 independent benchmarks$0.64 per solved taskModel BGLM 4.6Z.ai52.2/1002 independent benchmarksNo cost per solved task
Shared results
52
Gemini 2.5 Pro only
35
GLM 4.6 only
14
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 Pro 37.0 from 2 benchmarks, GLM 4.6 52.2 from 2 benchmarks.
Widest category
Agentic work, 22.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemini 2.5 Pro 54.1% against GLM 4.6 76.9%, 22.8 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against GLM 4.6 $2.20 per million output tokens, 4.5x apart.
Context window
Gemini 2.5 Pro 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 ProBarsGLM 4.6Ties
Coding46
Intelligence01
Agentic work01
Reasoning50
Math40
Knowledge60
Web design15
General190
All shared boards3913
CodingLike-for-likeFour of these boards feed the Vibe Coding Index46
Coding benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
SWE-bench Verified53.6%68.2%GLM 4.6
LMArena WebDev12261341GLM 4.6
AA Coding Index33.345.8GLM 4.6
LiveCodeBench (Vals AI)Not measured81.0%Only GLM 4.6 measured
SWE-bench Verified (Vals AI)54.4%Not measuredOnly Gemini 2.5 Pro measured
Vibe Code Bench (Vals AI)0.4%3.1%GLM 4.6
LiveCodeBench (Artificial Analysis run)80.1%69.5%Gemini 2.5 Pro
SciCode46.3%Not measuredOnly Gemini 2.5 Pro measured
Terminal-Bench Hard (Artificial Analysis run)26.5%28.8%GLM 4.6
Terminal-Bench32.6%24.5%Gemini 2.5 Pro
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro measured
WeirdML54.0%Not measuredOnly Gemini 2.5 Pro measured
ALE-BenchNot measured340.8Only GLM 4.6 measured
LMArena Text: coding14521449Gemini 2.5 Pro
LMArena Text: software and IT14591455Gemini 2.5 Pro
LMArena WebDev: HTML12351350GLM 4.6
LMArena WebDev: from an image1285Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
AA Intelligence Index16.118.5GLM 4.6
Epoch Capabilities Index145.1Not measuredOnly Gemini 2.5 Pro measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
AA Agentic Index1.6Not measuredOnly Gemini 2.5 Pro measured
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 Telecom54.1%76.9%GLM 4.6
GDPval23.3%Not measuredOnly Gemini 2.5 Pro measured
DeepResearch Bench41.5%Not measuredOnly Gemini 2.5 Pro measured
Vending-Bench 2$574Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
GPQA DiamondNot measured74.5%Only GLM 4.6 measured
GPQA Diamond (Artificial Analysis run)84.4%78.0%Gemini 2.5 Pro
Humanity's Last Exam (Artificial Analysis run)22.5%14.5%Gemini 2.5 Pro
GPQA Diamond (Epoch AI run)85.3%Not measuredOnly Gemini 2.5 Pro measured
ARC-AGI41.0%Not measuredOnly Gemini 2.5 Pro measured
ARC-AGI-24.9%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: hard prompts14551440Gemini 2.5 Pro
LMArena Text: expert14521432Gemini 2.5 Pro
LMArena Text: hard prompts in English14531445Gemini 2.5 Pro
LMArena Vision: diagrams1274Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: homework1281Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
AIMENot measured92.7%Only GLM 4.6 measured
MGSM (Vals AI)Not measured89.8%Only GLM 4.6 measured
AA Math Index87.786.0Gemini 2.5 Pro
AIME 2025 (Artificial Analysis run)87.7%86.0%Gemini 2.5 Pro
OTIS Mock AIME84.7%Not measuredOnly Gemini 2.5 Pro measured
FrontierMath, tiers 1 to 324.6%Not measuredOnly Gemini 2.5 Pro measured
FrontierMath, tier 40.0%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: math14501432Gemini 2.5 Pro
LMArena Text: mathematical work14541447Gemini 2.5 Pro
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
Knowledge benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
MMLU ProNot measured82.2%Only GLM 4.6 measured
LegalBench (Vals AI)Not measured79.6%Only GLM 4.6 measured
CaseLaw (Vals AI)63.9%Not measuredOnly Gemini 2.5 Pro measured
CorpFin (Vals AI)60.8%56.8%Gemini 2.5 Pro
TaxEval (Vals AI)Not measured66.2%Only GLM 4.6 measured
MortgageTax (Vals AI)68.9%Not measuredOnly Gemini 2.5 Pro measured
MedQA (Vals AI)Not measured92.2%Only GLM 4.6 measured
MedCode (Vals AI)50.6%Not measuredOnly Gemini 2.5 Pro measured
MMLU Pro (Artificial Analysis run)86.2%82.9%Gemini 2.5 Pro
LMArena Text: science14801456Gemini 2.5 Pro
LMArena Text: medicine and healthcare14761455Gemini 2.5 Pro
LMArena Text: legal and government14801448Gemini 2.5 Pro
LMArena Text: business and finance14391416Gemini 2.5 Pro
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index15
Web design benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
Design Arena: websites11671174GLM 4.6
Design Arena: UI components11391147GLM 4.6
Design Arena: game dev11121151GLM 4.6
Design Arena: data viz12221161Gemini 2.5 Pro
Design Arena: 3D10801129GLM 4.6
Design Arena: all code categories11521166GLM 4.6
Design Arena: SVGNot measured1108Only GLM 4.6 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for Gemini 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 4.6Leader
SAGE (Vals AI)41.9%Not measuredOnly Gemini 2.5 Pro measured
MedScribe (Vals AI)73.5%Not measuredOnly Gemini 2.5 Pro measured
IFBench48.7%43.4%Gemini 2.5 Pro
Long context reasoning (AA-LCR)69.0%54.0%Gemini 2.5 Pro
DTBench82.4%Not measuredOnly Gemini 2.5 Pro measured
LMCA34.8%Not measuredOnly Gemini 2.5 Pro measured
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text14581440Gemini 2.5 Pro
LMArena Text: instruction following14371410Gemini 2.5 Pro
LMArena Text: creative writing14541412Gemini 2.5 Pro
LMArena Vision1263Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: English14581449Gemini 2.5 Pro
LMArena Text: non-English14521426Gemini 2.5 Pro
LMArena Text: Chinese15071499Gemini 2.5 Pro
LMArena Text: German14871447Gemini 2.5 Pro
LMArena Text: Japanese14611393Gemini 2.5 Pro
LMArena Text: Korean14341400Gemini 2.5 Pro
LMArena Text: French14731459Gemini 2.5 Pro
LMArena Text: Spanish14741436Gemini 2.5 Pro
LMArena Text: Russian14611418Gemini 2.5 Pro
LMArena Text: Polish14791447Gemini 2.5 Pro
LMArena Text: multi-turn14531427Gemini 2.5 Pro
LMArena Text: longer queries14491422Gemini 2.5 Pro
LMArena Text: writing and language14541415Gemini 2.5 Pro
LMArena Text: entertainment and media14411409Gemini 2.5 Pro
LMArena Vision: English1261Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: Chinese1300Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: reading text1270Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: humor1262Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: captioning1304Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: recognizing things1283Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: creative writing1265Not measuredOnly Gemini 2.5 Pro measured
LMArena Document1421Not measuredOnly Gemini 2.5 Pro 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 2.5 Pro and GLM 4.6
BenchmarkGemini 2.5 ProGLM 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 Pro$0.0063Fits in one request
GLM 4.6$0.0016Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro$0.092Fits in one request
GLM 4.6$0.034Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro$0.350Fits in one request
GLM 4.6$0.132Exceeds the context window

GLM 4.6 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 Pro and GLM 4.6
SpecificationGoogle Gemini 2.5 ProZ.ai GLM 4.6
MakerGoogleZ.ai
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025September 30, 2025
Context window1.05M205K
Input $/Mtok$1.25$0.55
Output $/Mtok$10.00$2.20
Coding index37.052.2
Independent measurements behind it22
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro better than GLM 4.6 for coding?

Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro when the context window is larger, 1.05M against 205K tokens, or when what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench, where it leads.

Which is cheaper, Gemini 2.5 Pro or GLM 4.6?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; GLM 4.6 costs $0.55 and $2.20. Cost per solved task is known for Gemini 2.5 Pro only.

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

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

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

52 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 2 independent benchmarks 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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