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GLM 5.1 vs GPT-4o

Updated October 21, 2026. 12 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

GLM 5.1Z.ai
Coding
44.0
Overall
26.1
Output $/M
$4.40
12
GPT-4oOpenAI
Coding
38.8
Overall
No data
Output $/M
$10.00
0
vs boards won of 12 shared

Decision reading

Pick GLM 5.1 for coding: it scores 44.0 on the Vibe Coding Index against 38.8 for GPT-4o.

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

Shared results
12
GLM 5.1 only
77
GPT-4o only
14
Like-for-like categories
5 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 38.8 from 1 benchmark.
Widest category
Agentic work, 72.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 5.1 97.7% against GPT-4o 25.1%, 72.5 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against GPT-4o $10.00 per million output tokens, 2.3x apart.
Context window
GLM 5.1 takes 205K tokens, GPT-4o 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-4oTies
Coding10
Agentic work10
Reasoning20
Web design60
General20
All shared boards120
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
Coding benchmarks for GLM 5.1 and GPT-4o
BenchmarkGLM 5.1GPT-4oLeader
SWE-bench VerifiedNot measured38.8%Only GPT-4o measured
SWE-bench LiteNot measured38.0%Only GPT-4o measured
SWE-bench (full test set)Not measured18.8%Only GPT-4o measured
SWE-bench MultimodalNot measured30.4%Only GPT-4o 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 measured30.9%Only GPT-4o 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: coding1485Not measuredOnly GLM 5.1 measured
LMArena Text: software and IT1484Not measuredOnly GLM 5.1 measured
LMArena WebDev: React1505Not measuredOnly GLM 5.1 measured
LMArena WebDev: HTML1508Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 17 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for GLM 5.1 and GPT-4o
BenchmarkGLM 5.1GPT-4oLeader
AA Intelligence Index26.1Not measuredOnly GLM 5.1 measured
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
BenchmarkGLM 5.1GPT-4oLeader
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%25.1%GLM 5.1
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
GDPvalNot measured9.9%Only GPT-4o measured
Vending-Bench 2$5,634Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for GLM 5.1 and GPT-4o
BenchmarkGLM 5.1GPT-4oLeader
GPQA Diamond84.5%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Artificial Analysis run)86.8%54.3%GLM 5.1
Humanity's Last Exam (Artificial Analysis run)30.1%2.4%GLM 5.1
GPQA Diamond (Epoch AI run)89.9%Not measuredOnly GLM 5.1 measured
ARC-AGINot measured4.5%Only GPT-4o measured
ARC-AGI-2Not measured0.0%Only GPT-4o measured
SimpleBench55.1%Not measuredOnly GLM 5.1 measured
Chess puzzles20.0%Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts1473Not measuredOnly GLM 5.1 measured
LMArena Text: expert1478Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts in English1482Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 10 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Math benchmarks for GLM 5.1 and GPT-4o
BenchmarkGLM 5.1GPT-4oLeader
AIME91.9%Not measuredOnly GLM 5.1 measured
AA Math IndexNot measured6.0Only GPT-4o measured
AIME 2025 (Artificial Analysis run)Not measured6.0%Only GPT-4o measured
OTIS Mock AIME93.3%Not measuredOnly GLM 5.1 measured
FrontierMath, tiers 1 to 336.8%Not measuredOnly GLM 5.1 measured
ProofBench22.2%Not measuredOnly GLM 5.1 measured
LMArena Text: math1473Not measuredOnly GLM 5.1 measured
LMArena Text: mathematical work1470Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 5 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Knowledge benchmarks for GLM 5.1 and GPT-4o
BenchmarkGLM 5.1GPT-4oLeader
MMLU Pro86.9%Not measuredOnly GLM 5.1 measured
LegalBench (Vals AI)84.4%Not measuredOnly GLM 5.1 measured
CaseLaw (Vals AI)51.5%Not measuredOnly GLM 5.1 measured
CorpFin (Vals AI)64.5%Not measuredOnly GLM 5.1 measured
TaxEval (Vals AI)71.2%Not measuredOnly GLM 5.1 measured
MedCode (Vals AI)41.6%Not measuredOnly GLM 5.1 measured
MMLU Pro (Artificial Analysis run)Not measured74.8%Only GPT-4o measured
SimpleQA Verified34.0%Not measuredOnly GLM 5.1 measured
MMLUNot measured88.1%Only GPT-4o measured
LMArena Text: science1478Not measuredOnly GLM 5.1 measured
LMArena Text: medicine and healthcare1474Not measuredOnly GLM 5.1 measured
LMArena Text: legal and government1465Not measuredOnly GLM 5.1 measured
LMArena Text: business and finance1452Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for GLM 5.1 and GPT-4o
BenchmarkGLM 5.1GPT-4oLeader
Design Arena: websites1290831GLM 5.1
Design Arena: UI components1292885GLM 5.1
Design Arena: game dev1265906GLM 5.1
Design Arena: data viz1366858GLM 5.1
Design Arena: 3D1336869GLM 5.1
Design Arena: all code categories1268861GLM 5.1
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 index20
General benchmarks for GLM 5.1 and GPT-4o
BenchmarkGLM 5.1GPT-4oLeader
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%34.3%GLM 5.1
Long context reasoning (AA-LCR)73.7%49.3%GLM 5.1
DTBenchNot measured64.5%Only GPT-4o measured
LMCANot measured16.6%Only GPT-4o measured
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text1463Not measuredOnly GLM 5.1 measured
LMArena Text: instruction following1453Not measuredOnly GLM 5.1 measured
LMArena Text: creative writing1453Not measuredOnly GLM 5.1 measured
LMArena Text: English1476Not measuredOnly GLM 5.1 measured
LMArena Text: non-English1448Not measuredOnly GLM 5.1 measured
LMArena Text: Chinese1515Not measuredOnly GLM 5.1 measured
LMArena Text: German1467Not measuredOnly GLM 5.1 measured
LMArena Text: Japanese1435Not measuredOnly GLM 5.1 measured
LMArena Text: Korean1424Not measuredOnly GLM 5.1 measured
LMArena Text: French1470Not measuredOnly GLM 5.1 measured
LMArena Text: Spanish1468Not measuredOnly GLM 5.1 measured
LMArena Text: Russian1454Not measuredOnly GLM 5.1 measured
LMArena Text: Polish1449Not measuredOnly GLM 5.1 measured
LMArena Text: multi-turn1473Not measuredOnly GLM 5.1 measured
LMArena Text: longer queries1467Not measuredOnly GLM 5.1 measured
LMArena Text: writing and language1454Not measuredOnly GLM 5.1 measured
LMArena Text: entertainment and media1442Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 22 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
BenchmarkGLM 5.1GPT-4oLeader
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$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$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$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
SpecificationZ.ai GLM 5.1OpenAI GPT-4o
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 7, 2026May 13, 2024
Context window205K128K
Input $/Mtok$1.40$2.50
Output $/Mtok$4.40$10.00
Coding index44.038.8
Independent measurements behind it11
Cost per solved task$0.60Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than GPT-4o for coding?

Pick GLM 5.1 for coding: it scores 44.0 on the Vibe Coding Index against 38.8 for GPT-4o. GPT-4o 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?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; GPT-4o 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?

GLM 5.1, with 205K tokens against 128K.

How many benchmarks is the GLM 5.1 vs GPT-4o comparison based on?

12 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's on 1. Where only one model has a result, the page says so instead of naming a winner.

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