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GLM 4.6 vs GPT-5

GPT-5 leads GLM 4.6 on coding, 38.8 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 4.5x less per output token ($2.20 vs $10.00 per million). Updated October 22, 2026; 64 benchmarks have a result for both.

Replace GLM 4.6 Replace GPT-5
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
29
GPT-5OpenAI
Coding
38.8
Overall
51.5
Output $/M
$10.00
35
vs boards won of 64 shared

GLM 4.6 or GPT-5: which to pick

Pick GPT-5 for coding: it scores 38.8 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 4.5x cheaper ($2.20 vs $10.00 per million) and work measured by AA Coding Index or LMArena Text: coding, where it leads.

Model AGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved taskModel BGPT-5OpenAI38.8/1003 independent benchmarks$0.39 per solved task
Shared results
64
GLM 4.6 only
5
GPT-5 only
49
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
GLM 4.6 8.8 from 2 benchmarks, GPT-5 38.8 from 3 benchmarks.
Widest category
Agentic work, 20.7 points apart on average over 2 shared benchmarks.
Widest single gap
BrowseComp-Plus: GLM 4.6 48.2% against GPT-5 80.0%, 31.8 points apart on a 0 to 100 scale.
Output price
GLM 4.6 $2.20 against GPT-5 $10.00 per million output tokens, 4.5x apart.
Context window
GLM 4.6 takes 205K tokens, GPT-5 400K.

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
CategoryGLM 4.6BarsGPT-5Ties
Coding39
Intelligence01
Agentic work02
Reasoning34
Math24
Knowledge46
Web design16
General163
All shared boards2935
CodingLike-for-likeSix of these boards feed the Vibe Coding Index39
Coding benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
Aider polyglotNot measured88.0%Only GPT-5 measured
SWE-bench Verified68.2%74.4%GPT-5
LMArena WebDev13411418GPT-5
AA Coding Index45.837.8GLM 4.6
LiveCodeBench (Vals AI)81.0%85.9%GPT-5
SWE-bench Verified (Vals AI)Not measured69.0%Only GPT-5 measured
Vibe Code Bench (Vals AI)3.1%20.1%GPT-5
LiveCodeBench (Artificial Analysis run)69.5%84.6%GPT-5
Terminal-Bench Hard (Artificial Analysis run)28.8%37.9%GPT-5
Terminal-Bench24.5%49.6%GPT-5
GSO-BenchNot measured6.9%Only GPT-5 measured
WeirdMLNot measured60.7%Only GPT-5 measured
ALE-Bench340.8807.6GPT-5
LMArena Text: coding14491436GLM 4.6
LMArena Text: software and IT14551420GLM 4.6
LMArena WebDev: HTML13501427GPT-5
SciCodeNot measured0.0%Only GPT-5 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
AA Intelligence Index18.523.0GPT-5
Epoch Capabilities IndexNot measured150.0Only GPT-5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
Design Arena: agents building full-stack apps1029Not measuredOnly GLM 4.6 measured
Design Arena: agents building mobile apps1096Not measuredOnly GLM 4.6 measured
Design Arena: agents building Android apps1084Not measuredOnly GLM 4.6 measured
Design Arena: agents building Godot games1180Not measuredOnly GLM 4.6 measured
τ²-Bench Telecom76.9%86.5%GPT-5
METR time horizonsNot measured69.6%Only GPT-5 measured
Remote Labor IndexNot measured1.7%Only GPT-5 measured
GDPvalNot measured34.8%Only GPT-5 measured
BALROGNot measured32.8%Only GPT-5 measured
DeepResearch BenchNot measured49.6%Only GPT-5 measured
Berkeley Function Calling Leaderboard (BFCL)72.4%Not measuredOnly GLM 4.6 measured
BrowseComp-Plus48.2%80.0%GPT-5
Neither model has a result on the other 29 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
Reasoning benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
GPQA Diamond74.5%85.6%GPT-5
MMMU Pro (Vals AI)Not measured81.5%Only GPT-5 measured
GPQA Diamond (Artificial Analysis run)78.0%85.4%GPT-5
Humanity's Last Exam (Artificial Analysis run)14.5%28.5%GPT-5
GPQA Diamond (Epoch AI run)Not measured86.2%Only GPT-5 measured
ARC-AGINot measured65.7%Only GPT-5 measured
ARC-AGI-2Not measured9.9%Only GPT-5 measured
SimpleBenchNot measured56.7%Only GPT-5 measured
Chess puzzlesNot measured36.0%Only GPT-5 measured
Mystery game puzzlesNot measured23.0%Only GPT-5 measured
EBR-benchNot measured12.7%Only GPT-5 measured
VPCTNot measured66.0%Only GPT-5 measured
LMArena Text: hard prompts14401415GLM 4.6
LMArena Text: expert14321419GLM 4.6
LMArena Text: hard prompts in English14451419GLM 4.6
LMArena Vision: diagramsNot measured1252Only GPT-5 measured
LMArena Vision: homeworkNot measured1278Only GPT-5 measured
Kagi LLM Benchmark45.7%72.7%GPT-5
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index24
Math benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
AIME92.7%93.4%GPT-5
MATH 500 (Vals AI)Not measured96.0%Only GPT-5 measured
MGSM (Vals AI)89.8%92.8%GPT-5
AA Math Index86.094.3GPT-5
AIME 2025 (Artificial Analysis run)86.0%94.3%GPT-5
OTIS Mock AIMENot measured91.4%Only GPT-5 measured
FrontierMath, tiers 1 to 3Not measured55.4%Only GPT-5 measured
FrontierMath, tier 4Not measured22.0%Only GPT-5 measured
ProofBenchNot measured18.0%Only GPT-5 measured
MATH level 5Not measured98.1%Only GPT-5 measured
LMArena Text: math14321407GLM 4.6
LMArena Text: mathematical work14471405GLM 4.6
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index46
Knowledge benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
MMLU Pro82.2%86.5%GPT-5
LegalBench (Vals AI)79.6%86.0%GPT-5
CaseLaw (Vals AI)Not measured66.5%Only GPT-5 measured
CorpFin (Vals AI)56.8%61.1%GPT-5
TaxEval (Vals AI)66.2%73.4%GPT-5
MortgageTax (Vals AI)Not measured65.5%Only GPT-5 measured
MedQA (Vals AI)92.2%96.3%GPT-5
MedCode (Vals AI)Not measured49.6%Only GPT-5 measured
MMLU Pro (Artificial Analysis run)82.9%87.1%GPT-5
SimpleQA VerifiedNot measured50.1%Only GPT-5 measured
GeoBenchNot measured81.0%Only GPT-5 measured
LMArena Text: science14561416GLM 4.6
LMArena Text: medicine and healthcare14551413GLM 4.6
LMArena Text: legal and government14481431GLM 4.6
LMArena Text: business and finance14161400GLM 4.6
FACTS Benchmark SuiteNot measured56.5%Only GPT-5 measured
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index16
Web design benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
Design Arena: websites11741184GPT-5
Design Arena: UI components11451177GPT-5
Design Arena: game dev11501185GPT-5
Design Arena: data viz11611221GPT-5
Design Arena: 3D11281055GLM 4.6
Design Arena: all code categories11651167GPT-5
Design Arena: SVG11081188GPT-5
Design Arena: ASCII artNot measured1141Only GPT-5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index163
General benchmarks for GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
SAGE (Vals AI)Not measured43.7%Only GPT-5 measured
MedScribe (Vals AI)Not measured83.7%Only GPT-5 measured
IFBench43.4%73.1%GPT-5
Long context reasoning (AA-LCR)54.0%78.2%GPT-5
DTBenchNot measured90.7%Only GPT-5 measured
LMCANot measured40.0%Only GPT-5 measured
Fiction.LiveBenchNot measured97.2%Only GPT-5 measured
Creative writing (Lech Mazur)Not measured86.0%Only GPT-5 measured
LMArena Text14401406GLM 4.6
LMArena Text: instruction following14101388GLM 4.6
LMArena Text: creative writing14121365GLM 4.6
LMArena VisionNot measured1232Only GPT-5 measured
LMArena Text: English14491409GLM 4.6
LMArena Text: non-English14261397GLM 4.6
LMArena Text: Chinese14991422GLM 4.6
LMArena Text: German14471416GLM 4.6
LMArena Text: Japanese13931409GPT-5
LMArena Text: Korean14001360GLM 4.6
LMArena Text: French14591409GLM 4.6
LMArena Text: Spanish14361399GLM 4.6
LMArena Text: Russian14181407GLM 4.6
LMArena Text: Polish14471431GLM 4.6
LMArena Text: multi-turn14271426GLM 4.6
LMArena Text: longer queries14221399GLM 4.6
LMArena Text: writing and language14151384GLM 4.6
LMArena Text: entertainment and media14091379GLM 4.6
LMArena Vision: EnglishNot measured1231Only GPT-5 measured
LMArena Vision: ChineseNot measured1267Only GPT-5 measured
LMArena Vision: reading textNot measured1246Only GPT-5 measured
LMArena Vision: humorNot measured1219Only GPT-5 measured
LMArena Vision: captioningNot measured1212Only GPT-5 measured
LMArena Vision: recognizing thingsNot measured1263Only GPT-5 measured
LMArena Vision: creative writingNot measured1210Only GPT-5 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 GLM 4.6 and GPT-5
BenchmarkGLM 4.6GPT-5Leader
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

GLM 4.6$0.0017Fits in one request
GPT-5$0.0063Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

GLM 4.6$0.037Fits in one request
GPT-5$0.092Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

GLM 4.6$0.142Exceeds the context window
GPT-5$0.350Fits in one request

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 GLM 4.6 and GPT-5
SpecificationZ.ai GLM 4.6OpenAI GPT-5
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedSeptember 30, 2025August 7, 2025
Context window205K400K
Input $/Mtok$0.60$1.25
Output $/Mtok$2.20$10.00
Coding index8.838.8
Independent measurements behind it23
Cost per solved taskNot computable$0.39
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.6 better than GPT-5 for coding?

Pick GPT-5 for coding: it scores 38.8 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 4.5x cheaper ($2.20 vs $10.00 per million) and work measured by AA Coding Index or LMArena Text: coding, where it leads.

Which is cheaper, GLM 4.6 or GPT-5?

GLM 4.6 costs $0.60 per million input tokens and $2.20 per million output tokens; GPT-5 costs $1.25 and $10.00. Cost per solved task is known for GPT-5 only.

Which has the bigger context window, GLM 4.6 or GPT-5?

GPT-5, with 400K tokens against 205K.

How many benchmarks is the GLM 4.6 vs GPT-5 comparison based on?

64 benchmarks have a result for both models as of October 22, 2026. GLM 4.6's coding index rests on 2 independent benchmarks and GPT-5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/glm-4-6-vs-gpt-5">LLMBenchmark.ai, GLM 4.6 vs GPT-5</a></p>