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GLM 4.5V vs Grok 4.20

Grok 4.20 leads GLM 4.5V on the Artificial Analysis Intelligence Index, 25.7 to 7.6, and GLM 4.5V costs 1.4x less per output token ($1.80 vs $2.50 per million). Updated October 21, 2026; 7 benchmarks have a result for both.

Replace GLM 4.5V Replace Grok 4.20
GLM 4.5VZ.ai
Coding
No data
Overall
7.6
Output $/M
$1.80
0
Grok 4.20xAI
Coding
33.3
Overall
25.7
Output $/M
$2.50
7
vs boards won of 7 shared

GLM 4.5V or Grok 4.20: which to pick

Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding.

Pick GLM 4.5V for output tokens 1.4x cheaper ($1.80 vs $2.50 per million).

Model AGLM 4.5VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGrok 4.20xAI33.3/1002 independent benchmarks$0.72 per solved task
Shared results
7
GLM 4.5V only
33
Grok 4.20 only
47
Like-for-like categories
5 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 4.5V not benchmarked, Grok 4.20 33.3 from 2 benchmarks.
Widest category
Agentic work, 70.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5V 22.5% against Grok 4.20 93.0%, 70.5 points apart on a 0 to 100 scale.
Output price
GLM 4.5V $1.80 against Grok 4.20 $2.50 per million output tokens, 1.4x apart.
Context window
GLM 4.5V takes 66K tokens, Grok 4.20 2M.

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 4.5VBarsGrok 4.20Ties
Coding01
Intelligence01
Agentic work01
Reasoning02
General02
All shared boards07
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
LiveCodeBench (Vals AI)Not measured84.3%Only Grok 4.20 measured
SWE-bench Verified (Vals AI)Not measured72.2%Only Grok 4.20 measured
Vibe Code Bench (Vals AI)Not measured4.1%Only Grok 4.20 measured
Code migration (Vals AI)Not measured0.3%Only Grok 4.20 measured
Terminal-Bench 2.1 (Vals AI)Not measured44.2%Only Grok 4.20 measured
LiveCodeBench (Artificial Analysis run)60.4%Not measuredOnly GLM 4.5V measured
Terminal-Bench Hard (Artificial Analysis run)6.8%37.9%Grok 4.20
Terminal-BenchNot measured57.3%Only Grok 4.20 measured
WeirdMLNot measured52.3%Only Grok 4.20 measured
LMArena Text: coding1347Not measuredOnly GLM 4.5V measured
LMArena Text: software and IT1353Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
AA Intelligence Index7.625.7Grok 4.20
Epoch Capabilities IndexNot measured152.1Only Grok 4.20 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
Design Arena: agents building web appsNot measured1144Only Grok 4.20 measured
Design Arena: agents building full-stack appsNot measured1054Only Grok 4.20 measured
Design Arena: agents building mobile appsNot measured1090Only Grok 4.20 measured
Design Arena: agents building Android appsNot measured1052Only Grok 4.20 measured
Design Arena: agents building Godot gamesNot measured1089Only Grok 4.20 measured
Design Arena: HTML slidesNot measured1180Only Grok 4.20 measured
Finance Agent (Vals AI)Not measured28.5%Only Grok 4.20 measured
Tax Agent Bench (Vals AI)Not measured7.0%Only Grok 4.20 measured
Legal Research Bench (Vals AI)Not measured13.9%Only Grok 4.20 measured
Excel Modeling Benchmark (Vals AI)Not measured11.7%Only Grok 4.20 measured
τ²-Bench Telecom22.5%93.0%Grok 4.20
Vending-Bench 2Not measured$4,663Only Grok 4.20 measured
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
GPQA DiamondNot measured88.6%Only Grok 4.20 measured
MMMU Pro (Vals AI)Not measured83.5%Only Grok 4.20 measured
GPQA Diamond (Artificial Analysis run)68.4%91.1%Grok 4.20
Humanity's Last Exam (Artificial Analysis run)6.3%34.5%Grok 4.20
ARC-AGINot measured89.5%Only Grok 4.20 measured
ARC-AGI-2Not measured65.1%Only Grok 4.20 measured
LMArena Text: hard prompts1335Not measuredOnly GLM 4.5V measured
LMArena Text: expert1353Not measuredOnly GLM 4.5V measured
LMArena Text: hard prompts in English1357Not measuredOnly GLM 4.5V measured
LMArena Vision: diagrams1151Not measuredOnly GLM 4.5V measured
LMArena Vision: homework1163Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 10 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
AIMENot measured96.5%Only Grok 4.20 measured
AA Math Index73.0Not measuredOnly GLM 4.5V measured
AIME 2025 (Artificial Analysis run)73.0%Not measuredOnly GLM 4.5V measured
LMArena Text: math1354Not measuredOnly GLM 4.5V measured
LMArena Text: mathematical work1336Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Knowledge benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
MMLU ProNot measured86.3%Only Grok 4.20 measured
LegalBench (Vals AI)Not measured77.7%Only Grok 4.20 measured
CaseLaw (Vals AI)Not measured54.4%Only Grok 4.20 measured
CorpFin (Vals AI)Not measured63.7%Only Grok 4.20 measured
TaxEval (Vals AI)Not measured74.1%Only Grok 4.20 measured
MortgageTax (Vals AI)Not measured45.4%Only Grok 4.20 measured
MedQA (Vals AI)Not measured94.5%Only Grok 4.20 measured
MedCode (Vals AI)Not measured32.2%Only Grok 4.20 measured
MMLU Pro (Artificial Analysis run)78.8%Not measuredOnly GLM 4.5V measured
LMArena Text: science1330Not measuredOnly GLM 4.5V measured
LMArena Text: medicine and healthcare1349Not measuredOnly GLM 4.5V measured
LMArena Text: legal and government1338Not measuredOnly GLM 4.5V measured
LMArena Text: business and finance1309Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
Design Arena: websitesNot measured1229Only Grok 4.20 measured
Design Arena: UI componentsNot measured1199Only Grok 4.20 measured
Design Arena: game devNot measured1192Only Grok 4.20 measured
Design Arena: data vizNot measured1217Only Grok 4.20 measured
Design Arena: 3DNot measured1193Only Grok 4.20 measured
Design Arena: all code categoriesNot measured1221Only Grok 4.20 measured
Design Arena: SVGNot measured1164Only Grok 4.20 measured
Design Arena: ASCII artNot measured1174Only Grok 4.20 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for GLM 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
SAGE (Vals AI)Not measured38.2%Only Grok 4.20 measured
MedScribe (Vals AI)Not measured63.4%Only Grok 4.20 measured
Vals Multimodal IndexNot measured39.1%Only Grok 4.20 measured
IFBench34.2%81.2%Grok 4.20
Long context reasoning (AA-LCR)0.0%69.0%Grok 4.20
DTBenchNot measured90.1%Only Grok 4.20 measured
LMCANot measured38.7%Only Grok 4.20 measured
CL-benchNot measured22.2%Only Grok 4.20 measured
CL-bench LifeNot measured11.9%Only Grok 4.20 measured
LMArena Text1333Not measuredOnly GLM 4.5V measured
LMArena Text: instruction following1311Not measuredOnly GLM 4.5V measured
LMArena Text: creative writing1294Not measuredOnly GLM 4.5V measured
LMArena Vision1154Not measuredOnly GLM 4.5V measured
LMArena Text: English1362Not measuredOnly GLM 4.5V measured
LMArena Text: non-English1303Not measuredOnly GLM 4.5V measured
LMArena Text: Chinese1337Not measuredOnly GLM 4.5V measured
LMArena Text: Spanish1336Not measuredOnly GLM 4.5V measured
LMArena Text: Russian1298Not measuredOnly GLM 4.5V measured
LMArena Text: Polish1302Not measuredOnly GLM 4.5V measured
LMArena Text: multi-turn1333Not measuredOnly GLM 4.5V measured
LMArena Text: longer queries1305Not measuredOnly GLM 4.5V measured
LMArena Text: writing and language1302Not measuredOnly GLM 4.5V measured
LMArena Text: entertainment and media1303Not measuredOnly GLM 4.5V measured
LMArena Vision: English1183Not measuredOnly GLM 4.5V measured
LMArena Vision: reading text1151Not measuredOnly GLM 4.5V 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 4.5V and Grok 4.20
BenchmarkGLM 4.5VGrok 4.20Leader
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 4.5V$0.0015Fits in one request
Grok 4.20$0.0025Fits in one request

GLM 4.5V costs less

Repository review

50K input + 3K output tokens

GLM 4.5V$0.035Fits in one request
Grok 4.20$0.070Fits in one request

GLM 4.5V costs less

Agent loop

200K input + 10K output tokens

GLM 4.5V$0.138Exceeds the context window
Grok 4.20$0.275Fits in one request

GLM 4.5V 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 4.5V and Grok 4.20
SpecificationZ.ai GLM 4.5VSpaceXAI Grok 4.20
MakerZ.aixAI
WeightsOpen weightsNo public weights listed
ReleasedAugust 11, 2025March 31, 2026
Context window66K2M
Input $/Mtok$0.60$1.25
Output $/Mtok$1.80$2.50
Coding indexNot benchmarked33.3
Independent measurements behind it02
Cost per solved taskNot computable$0.72
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5V better than Grok 4.20 for coding?

Only Grok 4.20 has a coding score, 33.3 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding. Pick GLM 4.5V for output tokens 1.4x cheaper ($1.80 vs $2.50 per million).

Which is cheaper, GLM 4.5V or Grok 4.20?

GLM 4.5V costs $0.60 per million input tokens and $1.80 per million output tokens; Grok 4.20 costs $1.25 and $2.50. Cost per solved task is known for Grok 4.20 only.

Which has the bigger context window, GLM 4.5V or Grok 4.20?

Grok 4.20, with 2M tokens against 66K.

How many benchmarks is the GLM 4.5V vs Grok 4.20 comparison based on?

7 benchmarks have a result for both models as of October 21, 2026. GLM 4.5V's coding index rests on 0 independent benchmarks and Grok 4.20's on 2. Where only one model has a result, the page says so instead of naming a winner.

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