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GLM 5.1 vs GPT-4o (2024-08-06)

Updated October 21, 2026. 45 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 5.1 Replace GPT-4o (2024-08-06)
GLM 5.1Z.ai
Coding
44.0
Overall
26.1
Output $/M
$4.40
45
GPT-4o (2024-08-06)OpenAI
Coding
23.1
Overall
7.7
Output $/M
$10.00
0
vs boards won of 45 shared

Decision reading

Pick GLM 5.1 for coding: it scores 44.0 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06).

GPT-4o (2024-08-06) is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Model AGLM 5.1Z.ai44.0/1001 independent benchmark$0.60 per solved taskModel BGPT-4o (2024-08-06)OpenAI23.1/1001 independent benchmarkNo cost per solved task
Shared results
45
GLM 5.1 only
44
GPT-4o (2024-08-06) only
13
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 5.1 44.0 from 1 benchmark, GPT-4o (2024-08-06) 23.1 from 1 benchmark.
Widest category
Agentic work, 68.7 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: GLM 5.1 93.3% against GPT-4o (2024-08-06) 6.4%, 86.9 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against GPT-4o (2024-08-06) $10.00 per million output tokens, 2.3x apart.
Context window
GLM 5.1 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 5.1BarsGPT-4o (2024-08-06)Ties
Coding30
Intelligence10
Agentic work10
Reasoning80
Math50
Knowledge90
General180
All shared boards450
CodingLike-for-likeFour of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
Aider polyglotNot measured23.1%Only GPT-4o (2024-08-06) measured
SWE-bench LiteNot measured21.7%Only GPT-4o (2024-08-06) measured
LMArena WebDev1508Not measuredOnly GLM 5.1 measured
AA Coding Index55.8Not measuredOnly GLM 5.1 measured
LiveCodeBench (Vals AI)81.4%Not measuredOnly GLM 5.1 measured
SWE-bench Verified (Vals AI)76.4%Not measuredOnly GLM 5.1 measured
Vibe Code Bench (Vals AI)31.5%Not measuredOnly GLM 5.1 measured
Code migration (Vals AI)25.8%Not measuredOnly GLM 5.1 measured
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)56.9%Not measuredOnly GLM 5.1 measured
LiveCodeBench (Artificial Analysis run)Not measured31.7%Only GPT-4o (2024-08-06) measured
SciCode44.8%Not measuredOnly GLM 5.1 measured
Terminal-Bench Hard (Artificial Analysis run)43.2%8.3%GLM 5.1
WeirdML57.1%Not measuredOnly GLM 5.1 measured
ALE-Bench887.1Not measuredOnly GLM 5.1 measured
LMArena Text: coding14851283GLM 5.1
LMArena Text: software and IT14841278GLM 5.1
LMArena WebDev: React1505Not measuredOnly GLM 5.1 measured
LMArena WebDev: HTML1508Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
AA Intelligence Index26.17.7GLM 5.1
Epoch Capabilities Index149.8Not measuredOnly GLM 5.1 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
AA Agentic Index23.9Not measuredOnly GLM 5.1 measured
Design Arena: agents building web apps1175Not measuredOnly GLM 5.1 measured
Design Arena: agents building full-stack apps1167Not measuredOnly GLM 5.1 measured
Design Arena: agents building mobile apps1162Not measuredOnly GLM 5.1 measured
Design Arena: agents building Android apps1186Not measuredOnly GLM 5.1 measured
Design Arena: agents building Godot games1053Not measuredOnly GLM 5.1 measured
Design Arena: agents building games1164Not measuredOnly GLM 5.1 measured
Design Arena: HTML slides1170Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1189Not measuredOnly GLM 5.1 measured
Design Arena: spreadsheets1315Not measuredOnly GLM 5.1 measured
Finance Agent (Vals AI)44.8%Not measuredOnly GLM 5.1 measured
Legal Research Bench (Vals AI)27.9%Not measuredOnly GLM 5.1 measured
τ²-Bench Telecom97.7%28.9%GLM 5.1
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
Vending-Bench 2$5,634Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
Reasoning benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
GPQA Diamond84.5%Not measuredOnly GLM 5.1 measured
MMMU Pro (Vals AI)Not measured64.0%Only GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)86.8%52.1%GLM 5.1
Humanity's Last Exam (Artificial Analysis run)30.1%2.3%GLM 5.1
GPQA Diamond (Epoch AI run)89.9%49.2%GLM 5.1
SimpleBench55.1%17.8%GLM 5.1
Chess puzzles20.0%6.0%GLM 5.1
LMArena Text: hard prompts14731264GLM 5.1
LMArena Text: expert14781241GLM 5.1
LMArena Text: hard prompts in English14821277GLM 5.1
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index50
Math benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
AIME91.9%14.0%GLM 5.1
MATH 500 (Vals AI)Not measured75.2%Only GPT-4o (2024-08-06) measured
MGSM (Vals AI)Not measured90.7%Only GPT-4o (2024-08-06) measured
OTIS Mock AIME93.3%6.4%GLM 5.1
FrontierMath, tiers 1 to 336.8%0.4%GLM 5.1
ProofBench22.2%Not measuredOnly GLM 5.1 measured
MATH level 5Not measured53.3%Only GPT-4o (2024-08-06) measured
LMArena Text: math14731285GLM 5.1
LMArena Text: mathematical work14701283GLM 5.1
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90
Knowledge benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
MMLU Pro86.9%74.1%GLM 5.1
LegalBench (Vals AI)84.4%80.1%GLM 5.1
CaseLaw (Vals AI)51.5%Not measuredOnly GLM 5.1 measured
CorpFin (Vals AI)64.5%39.4%GLM 5.1
TaxEval (Vals AI)71.2%71.1%GLM 5.1
MortgageTax (Vals AI)Not measured61.0%Only GPT-4o (2024-08-06) measured
MedQA (Vals AI)Not measured88.2%Only GPT-4o (2024-08-06) measured
MedCode (Vals AI)41.6%Not measuredOnly GLM 5.1 measured
SimpleQA Verified34.0%26.0%GLM 5.1
MMLUNot measured84.3%Only GPT-4o (2024-08-06) measured
LMArena Text: science14781274GLM 5.1
LMArena Text: medicine and healthcare14741252GLM 5.1
LMArena Text: legal and government14651275GLM 5.1
LMArena Text: business and finance14521232GLM 5.1
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
Design Arena: websites1290Not measuredOnly GLM 5.1 measured
Design Arena: UI components1292Not measuredOnly GLM 5.1 measured
Design Arena: game dev1265Not measuredOnly GLM 5.1 measured
Design Arena: data viz1366Not measuredOnly GLM 5.1 measured
Design Arena: 3D1336Not measuredOnly GLM 5.1 measured
Design Arena: all code categories1268Not measuredOnly GLM 5.1 measured
Design Arena: SVG1217Not measuredOnly GLM 5.1 measured
Design Arena: ASCII art1142Not measuredOnly GLM 5.1 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 GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-4o (2024-08-06)Leader
Public Benefits Bench (Vals AI)61.8%Not measuredOnly GLM 5.1 measured
MedScribe (Vals AI)72.3%Not measuredOnly GLM 5.1 measured
IFBench76.3%36.0%GLM 5.1
Long context reasoning (AA-LCR)73.7%41.0%GLM 5.1
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text14631283GLM 5.1
LMArena Text: instruction following14531267GLM 5.1
LMArena Text: creative writing14531274GLM 5.1
LMArena VisionNot measured1065Only GPT-4o (2024-08-06) measured
LMArena Text: English14761297GLM 5.1
LMArena Text: non-English14481262GLM 5.1
LMArena Text: Chinese15151254GLM 5.1
LMArena Text: German14671257GLM 5.1
LMArena Text: Japanese14351234GLM 5.1
LMArena Text: Korean14241218GLM 5.1
LMArena Text: French14701263GLM 5.1
LMArena Text: Spanish14681269GLM 5.1
LMArena Text: Russian14541272GLM 5.1
LMArena Text: Polish1449Not measuredOnly GLM 5.1 measured
LMArena Text: multi-turn14731279GLM 5.1
LMArena Text: longer queries14671283GLM 5.1
LMArena Text: writing and language14541290GLM 5.1
LMArena Text: entertainment and media14421267GLM 5.1
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 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.1 and GPT-4o (2024-08-06)
BenchmarkGLM 5.1GPT-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 5.1$0.0036Fits in one request
GPT-4o (2024-08-06)$0.0075Fits in one request

GLM 5.1 costs less

Repository review

50K input + 3K output tokens

GLM 5.1$0.083Fits in one request
GPT-4o (2024-08-06)$0.155Fits in one request

GLM 5.1 costs less

Agent loop

200K input + 10K output tokens

GLM 5.1$0.324Exceeds the context window
GPT-4o (2024-08-06)$0.600Exceeds the context window

GLM 5.1 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 5.1 and GPT-4o (2024-08-06)
SpecificationZ.ai GLM 5.1OpenAI GPT-4o (2024-08-06)
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 7, 2026August 6, 2024
Context window205K128K
Input $/Mtok$1.40$2.50
Output $/Mtok$4.40$10.00
Coding index44.023.1
Independent measurements behind it11
Cost per solved task$0.60Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than GPT-4o (2024-08-06) for coding?

Pick GLM 5.1 for coding: it scores 44.0 on the Vibe Coding Index against 23.1 for GPT-4o (2024-08-06). GPT-4o (2024-08-06) is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Which is cheaper, GLM 5.1 or GPT-4o (2024-08-06)?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; GPT-4o (2024-08-06) costs $2.50 and $10.00. Cost per solved task is known for GLM 5.1 only.

Which has the bigger context window, GLM 5.1 or GPT-4o (2024-08-06)?

GLM 5.1, with 205K tokens against 128K.

How many benchmarks is the GLM 5.1 vs GPT-4o (2024-08-06) comparison based on?

45 benchmarks have a result for both models as of October 21, 2026. GLM 5.1's coding index rests on 1 independent benchmark 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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