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GLM 4.6 vs GPT-4o (2024-08-06)

Updated October 21, 2026. 42 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.6 Replace GPT-4o (2024-08-06)
GLM 4.6Z.ai
Coding
52.2
Overall
18.5
Output $/M
$2.20
39
GPT-4o (2024-08-06)OpenAI
Coding
23.1
Overall
7.7
Output $/M
$10.00
3
vs boards won of 42 shared

Decision reading

Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06).

Pick GPT-4o (2024-08-06) when what matters is MGSM (Vals AI) or LegalBench (Vals AI), where it leads.

Model AGLM 4.6Z.ai52.2/1002 independent benchmarksNo cost per solved taskModel BGPT-4o (2024-08-06)OpenAI23.1/1001 independent benchmarkNo cost per solved task
Shared results
42
GLM 4.6 only
24
GPT-4o (2024-08-06) only
16
Like-for-like categories
7 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
GLM 4.6 52.2 from 2 benchmarks, GPT-4o (2024-08-06) 23.1 from 1 benchmark.
Widest category
Agentic work, 48.0 points apart on average over 1 shared benchmark.
Widest single gap
AIME: GLM 4.6 92.7% against GPT-4o (2024-08-06) 14.0%, 78.8 points apart on a 0 to 100 scale.
Output price
GLM 4.6 $2.20 against GPT-4o (2024-08-06) $10.00 per million output tokens, 4.5x apart.
Context window
GLM 4.6 takes 205K tokens, GPT-4o (2024-08-06) 128K.

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-4o (2024-08-06)Ties
Coding40
Intelligence10
Agentic work10
Reasoning50
Math31
Knowledge72
General180
All shared boards393
CodingLike-for-likeFour of these boards feed the Vibe Coding Index40
Coding benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
Aider polyglotNot measured23.1%Only GPT-4o (2024-08-06) measured
SWE-bench Verified68.2%Not measuredOnly GLM 4.6 measured
SWE-bench LiteNot measured21.7%Only GPT-4o (2024-08-06) measured
LMArena WebDev1341Not measuredOnly GLM 4.6 measured
AA Coding Index45.8Not measuredOnly GLM 4.6 measured
LiveCodeBench (Vals AI)81.0%Not measuredOnly GLM 4.6 measured
Vibe Code Bench (Vals AI)3.1%Not measuredOnly GLM 4.6 measured
LiveCodeBench (Artificial Analysis run)69.5%31.7%GLM 4.6
Terminal-Bench Hard (Artificial Analysis run)28.8%8.3%GLM 4.6
Terminal-Bench24.5%Not measuredOnly GLM 4.6 measured
ALE-Bench340.8Not measuredOnly GLM 4.6 measured
LMArena Text: coding14491283GLM 4.6
LMArena Text: software and IT14551278GLM 4.6
LMArena WebDev: HTML1350Not measuredOnly GLM 4.6 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
AA Intelligence Index18.57.7GLM 4.6
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
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 apps1090Not measuredOnly GLM 4.6 measured
Design Arena: agents building Godot games1180Not measuredOnly GLM 4.6 measured
τ²-Bench Telecom76.9%28.9%GLM 4.6
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
GPQA Diamond74.5%Not measuredOnly GLM 4.6 measured
MMMU Pro (Vals AI)Not measured64.0%Only GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)78.0%52.1%GLM 4.6
Humanity's Last Exam (Artificial Analysis run)14.5%2.3%GLM 4.6
GPQA Diamond (Epoch AI run)Not measured49.2%Only GPT-4o (2024-08-06) measured
SimpleBenchNot measured17.8%Only GPT-4o (2024-08-06) measured
Chess puzzlesNot measured6.0%Only GPT-4o (2024-08-06) measured
LMArena Text: hard prompts14401264GLM 4.6
LMArena Text: expert14321241GLM 4.6
LMArena Text: hard prompts in English14451277GLM 4.6
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index31
Math benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
AIME92.7%14.0%GLM 4.6
MATH 500 (Vals AI)Not measured75.2%Only GPT-4o (2024-08-06) measured
MGSM (Vals AI)89.8%90.7%GPT-4o (2024-08-06)
AA Math Index86.0Not measuredOnly GLM 4.6 measured
AIME 2025 (Artificial Analysis run)86.0%Not measuredOnly GLM 4.6 measured
OTIS Mock AIMENot measured6.4%Only GPT-4o (2024-08-06) measured
FrontierMath, tiers 1 to 3Not measured0.4%Only GPT-4o (2024-08-06) measured
MATH level 5Not measured53.3%Only GPT-4o (2024-08-06) measured
LMArena Text: math14321285GLM 4.6
LMArena Text: mathematical work14471283GLM 4.6
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index72
Knowledge benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
MMLU Pro82.2%74.1%GLM 4.6
LegalBench (Vals AI)79.6%80.1%GPT-4o (2024-08-06)
CorpFin (Vals AI)56.8%39.4%GLM 4.6
TaxEval (Vals AI)66.2%71.1%GPT-4o (2024-08-06)
MortgageTax (Vals AI)Not measured61.0%Only GPT-4o (2024-08-06) measured
MedQA (Vals AI)92.2%88.2%GLM 4.6
MMLU Pro (Artificial Analysis run)82.9%Not measuredOnly GLM 4.6 measured
SimpleQA VerifiedNot measured26.0%Only GPT-4o (2024-08-06) measured
MMLUNot measured84.3%Only GPT-4o (2024-08-06) measured
LMArena Text: science14561274GLM 4.6
LMArena Text: medicine and healthcare14551252GLM 4.6
LMArena Text: legal and government14481275GLM 4.6
LMArena Text: business and finance14161232GLM 4.6
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
Design Arena: websites1174Not measuredOnly GLM 4.6 measured
Design Arena: UI components1147Not measuredOnly GLM 4.6 measured
Design Arena: game dev1151Not measuredOnly GLM 4.6 measured
Design Arena: data viz1161Not measuredOnly GLM 4.6 measured
Design Arena: 3D1129Not measuredOnly GLM 4.6 measured
Design Arena: all code categories1166Not measuredOnly GLM 4.6 measured
Design Arena: SVG1108Not measuredOnly 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 index180
General benchmarks for GLM 4.6 and GPT-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
IFBench43.4%36.0%GLM 4.6
Long context reasoning (AA-LCR)54.0%41.0%GLM 4.6
LMArena Text14401283GLM 4.6
LMArena Text: instruction following14101267GLM 4.6
LMArena Text: creative writing14121274GLM 4.6
LMArena VisionNot measured1065Only GPT-4o (2024-08-06) measured
LMArena Text: English14491297GLM 4.6
LMArena Text: non-English14261262GLM 4.6
LMArena Text: Chinese14991254GLM 4.6
LMArena Text: German14471257GLM 4.6
LMArena Text: Japanese13931234GLM 4.6
LMArena Text: Korean14001218GLM 4.6
LMArena Text: French14591263GLM 4.6
LMArena Text: Spanish14361269GLM 4.6
LMArena Text: Russian14181272GLM 4.6
LMArena Text: Polish1447Not measuredOnly GLM 4.6 measured
LMArena Text: multi-turn14271279GLM 4.6
LMArena Text: longer queries14221283GLM 4.6
LMArena Text: writing and language14151290GLM 4.6
LMArena Text: entertainment and media14091267GLM 4.6
LMArena Vision: EnglishNot measured1072Only GPT-4o (2024-08-06) measured
LMArena Vision: ChineseNot measured1009Only GPT-4o (2024-08-06) measured
Neither model has a result on the other 24 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-4o (2024-08-06)
BenchmarkGLM 4.6GPT-4o (2024-08-06)Leader
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$0.0016Fits in one request
GPT-4o (2024-08-06)$0.0075Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

GLM 4.6$0.034Fits in one request
GPT-4o (2024-08-06)$0.155Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

GLM 4.6$0.132Exceeds the context window
GPT-4o (2024-08-06)$0.600Exceeds 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 GLM 4.6 and GPT-4o (2024-08-06)
SpecificationZ.ai GLM 4.6OpenAI GPT-4o (2024-08-06)
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedSeptember 30, 2025August 6, 2024
Context window205K128K
Input $/Mtok$0.55$2.50
Output $/Mtok$2.20$10.00
Coding index52.223.1
Independent measurements behind it21
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.6 better than GPT-4o (2024-08-06) for coding?

Pick GLM 4.6 for coding: it scores 52.2 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06). Pick GPT-4o (2024-08-06) when what matters is MGSM (Vals AI) or LegalBench (Vals AI), where it leads.

Which is cheaper, GLM 4.6 or GPT-4o (2024-08-06)?

GLM 4.6 costs $0.55 per million input tokens and $2.20 per million output tokens; GPT-4o (2024-08-06) costs $2.50 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.6 or GPT-4o (2024-08-06)?

GLM 4.6, with 205K tokens against 128K.

How many benchmarks is the GLM 4.6 vs GPT-4o (2024-08-06) comparison based on?

42 benchmarks have a result for both models as of October 21, 2026. GLM 4.6's coding index rests on 2 independent benchmarks and GPT-4o (2024-08-06)'s on 1. Where only one model has a result, the page says so instead of naming a winner.

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