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GLM 5V Turbo vs Grok 4.5

Updated October 21, 2026. 60 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

GLM 5V TurboZ.ai
Coding
28.8
Overall
23.5
Output $/M
$4.00
4
Grok 4.5xAI
Coding
75.5
Overall
38.8
Output $/M
$6.00
56
vs boards won of 60 shared

Decision reading

Pick Grok 4.5 for coding: it scores 75.5 on the Vibe Coding Index against 28.8 for GLM 5V Turbo.

Pick GLM 5V Turbo when output tokens cost 1.5x less, or when what matters is Design Arena: agents building Android apps or LMArena Text: English, where it leads.

Shared results
60
GLM 5V Turbo only
5
Grok 4.5 only
60
Like-for-like categories
8 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 5V Turbo 28.8 from 1 benchmark, Grok 4.5 75.5 from 2 benchmarks.
Widest category
Coding, 18.5 points apart on average over 6 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: GLM 5V Turbo 1356 against Grok 4.5 1567, 35.2 points apart on a 0 to 100 scale.
Output price
GLM 5V Turbo $4.00 against Grok 4.5 $6.00 per million output tokens, 1.5x apart.
Context window
GLM 5V Turbo takes 203K tokens, Grok 4.5 500K.

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 5V TurboBarsGrok 4.5Ties
Coding06
Intelligence01
Agentic work17
Reasoning07
Math02
Knowledge04
Web design08
General321
All shared boards456
CodingLike-for-likeFour of these boards feed the Vibe Coding Index06
Coding benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
LiveBench codingNot measured94.3%Only Grok 4.5 measured
LMArena WebDev14021553Grok 4.5
AA Coding IndexNot measured72.4Only Grok 4.5 measured
LiveCodeBench (Vals AI)Not measured87.3%Only Grok 4.5 measured
SWE-bench Verified (Vals AI)Not measured86.6%Only Grok 4.5 measured
Terminal-Bench 4 (Vals AI)Not measured8.6%Only Grok 4.5 measured
Vibe Code Bench (Vals AI)Not measured69.0%Only Grok 4.5 measured
Code migration (Vals AI)Not measured36.6%Only Grok 4.5 measured
ProgramBench (Vals AI)Not measured0.0%Only Grok 4.5 measured
IOI (Vals AI)Not measured40.6%Only Grok 4.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured67.8%Only Grok 4.5 measured
SkillsBench (Vals AI)Not measured66.0%Only Grok 4.5 measured
CyberBench (Vals AI)Not measured71.0%Only Grok 4.5 measured
SciCodeNot measured55.0%Only Grok 4.5 measured
Terminal-Bench Hard (Artificial Analysis run)32.6%Not measuredOnly GLM 5V Turbo measured
FrontierCodeNot measured42.4%Only Grok 4.5 measured
WeirdMLNot measured46.4%Only Grok 4.5 measured
ALE-BenchNot measured1309.3Only Grok 4.5 measured
LMArena Text: coding14661474Grok 4.5
LMArena Text: software and IT14601471Grok 4.5
LMArena WebDev: React13861556Grok 4.5
LMArena WebDev: HTML13561567Grok 4.5
LMArena WebDev: from an image14251562Grok 4.5
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
AA Intelligence Index23.538.8Grok 4.5
Epoch Capabilities IndexNot measured154.1Only Grok 4.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index17
Agentic work benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
AA Agentic IndexNot measured41.2Only Grok 4.5 measured
Design Arena: agents building web apps11241217Grok 4.5
Design Arena: agents building full-stack apps11491249Grok 4.5
Design Arena: agents building mobile apps11341221Grok 4.5
Design Arena: agents building Android apps12671242GLM 5V Turbo
Design Arena: agents building Godot games9571229Grok 4.5
Design Arena: agents building games11021235Grok 4.5
Design Arena: HTML slides11201204Grok 4.5
Design Arena: PowerPoint slides11521232Grok 4.5
LiveBench researchNot measured85.9%Only Grok 4.5 measured
LiveBench browserNot measured44.0%Only Grok 4.5 measured
LiveBench long agenticNot measured27.9%Only Grok 4.5 measured
SREBench (Vals AI)Not measured0.8%Only Grok 4.5 measured
Finance Agent (Vals AI)Not measured48.4%Only Grok 4.5 measured
Tax Agent Bench (Vals AI)Not measured24.9%Only Grok 4.5 measured
Legal Research Bench (Vals AI)Not measured38.0%Only Grok 4.5 measured
Excel Modeling Benchmark (Vals AI)Not measured52.9%Only Grok 4.5 measured
Time Horizon Index (Vals AI)Not measured6.3%Only Grok 4.5 measured
τ²-Bench Telecom98.5%Not measuredOnly GLM 5V Turbo measured
APEX-AgentsNot measured56.2%Only Grok 4.5 measured
PostTrainBenchNot measured23.4%Only Grok 4.5 measured
Vending-Bench 2Not measured$3,887Only Grok 4.5 measured
LMArena SearchNot measured1216Only Grok 4.5 measured
Neither model has a result on the other 16 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
GPQA DiamondNot measured92.9%Only Grok 4.5 measured
LiveBench reasoningNot measured87.2%Only Grok 4.5 measured
MMMU Pro (Vals AI)Not measured61.8%Only Grok 4.5 measured
GPQA Diamond (Artificial Analysis run)80.9%93.1%Grok 4.5
Humanity's Last Exam (Artificial Analysis run)17.1%42.7%Grok 4.5
GPQA Diamond (Epoch AI run)Not measured93.4%Only Grok 4.5 measured
ARC-AGINot measured87.2%Only Grok 4.5 measured
ARC-AGI-2Not measured52.6%Only Grok 4.5 measured
SimpleBenchNot measured70.0%Only Grok 4.5 measured
Chess puzzlesNot measured35.0%Only Grok 4.5 measured
LMArena Text: hard prompts14431462Grok 4.5
LMArena Text: expert14531465Grok 4.5
LMArena Text: hard prompts in English14561464Grok 4.5
LMArena Vision: diagrams12861304Grok 4.5
LMArena Vision: homework12731295Grok 4.5
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
OTIS Mock AIMENot measured97.8%Only Grok 4.5 measured
FrontierMath, tiers 1 to 3Not measured57.2%Only Grok 4.5 measured
FrontierMath, tier 4Not measured24.4%Only Grok 4.5 measured
ProofBenchNot measured31.0%Only Grok 4.5 measured
LMArena Text: math14421460Grok 4.5
LMArena Text: mathematical work14471482Grok 4.5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
MMLU ProNot measured89.2%Only Grok 4.5 measured
LegalBench (Vals AI)Not measured86.0%Only Grok 4.5 measured
CorpFin (Vals AI)Not measured67.4%Only Grok 4.5 measured
TaxEval (Vals AI)Not measured71.7%Only Grok 4.5 measured
MortgageTax (Vals AI)Not measured61.8%Only Grok 4.5 measured
MedCode (Vals AI)Not measured43.3%Only Grok 4.5 measured
SimpleQA VerifiedNot measured48.3%Only Grok 4.5 measured
LMArena Text: science14481464Grok 4.5
LMArena Text: medicine and healthcare14331440Grok 4.5
LMArena Text: legal and government14361463Grok 4.5
LMArena Text: business and finance14351441Grok 4.5
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
Design Arena: websites12301281Grok 4.5
Design Arena: UI components12131279Grok 4.5
Design Arena: game dev12191263Grok 4.5
Design Arena: data viz12021267Grok 4.5
Design Arena: 3D12091257Grok 4.5
Design Arena: all code categories12281276Grok 4.5
Design Arena: SVG11511215Grok 4.5
Design Arena: ASCII art11181257Grok 4.5
LiveBench designNot measured78.1%Only Grok 4.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index321
General benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
LiveBench data analysisNot measured73.0%Only Grok 4.5 measured
SAGE (Vals AI)Not measured35.0%Only Grok 4.5 measured
MedScribe (Vals AI)Not measured86.9%Only Grok 4.5 measured
Vals Multimodal IndexNot measured63.4%Only Grok 4.5 measured
IFBench61.1%Not measuredOnly GLM 5V Turbo measured
Long context reasoning (AA-LCR)70.3%79.3%Grok 4.5
DTBenchNot measured96.5%Only Grok 4.5 measured
LMCANot measured45.2%Only Grok 4.5 measured
Surface Evolver BenchNot measured74.4%Only Grok 4.5 measured
Furniture assemblyNot measured22.5%Only Grok 4.5 measured
LMArena Text14371448Grok 4.5
LMArena Text: instruction following14231445Grok 4.5
LMArena Text: creative writing14171442Grok 4.5
LMArena Vision12641287Grok 4.5
LMArena Text: English14541453GLM 5V Turbo
LMArena Text: non-English14201440Grok 4.5
LMArena Text: Chinese14911495Grok 4.5
LMArena Text: German14221448Grok 4.5
LMArena Text: JapaneseNot measured1430Only Grok 4.5 measured
LMArena Text: Korean13971406Grok 4.5
LMArena Text: French14431457Grok 4.5
LMArena Text: Spanish14521451GLM 5V Turbo
LMArena Text: Russian14321449Grok 4.5
LMArena Text: Polish14321432GLM 5V Turbo
LMArena Text: multi-turn14311456Grok 4.5
LMArena Text: longer queries14381462Grok 4.5
LMArena Text: writing and language14201445Grok 4.5
LMArena Text: entertainment and media14071434Grok 4.5
LMArena Vision: English12741285Grok 4.5
LMArena Vision: Chinese13291345Grok 4.5
LMArena Vision: reading text12701293Grok 4.5
LMArena Vision: humor12681276Grok 4.5
LMArena Vision: captioning1264Not measuredOnly GLM 5V Turbo measured
LMArena Vision: recognizing things1241Not measuredOnly GLM 5V Turbo measured
LMArena Vision: creative writing12521293Grok 4.5
LMArena Document14161452Grok 4.5
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5V Turbo and Grok 4.5
BenchmarkGLM 5V TurboGrok 4.5Leader
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 5V Turbo$0.0032Fits in one request
Grok 4.5$0.0050Fits in one request

GLM 5V Turbo costs less

Repository review

50K input + 3K output tokens

GLM 5V Turbo$0.072Fits in one request
Grok 4.5$0.118Fits in one request

GLM 5V Turbo costs less

Agent loop

200K input + 10K output tokens

GLM 5V Turbo$0.280Exceeds the context window
Grok 4.5$0.460Fits in one request

GLM 5V Turbo 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 5V Turbo and Grok 4.5
SpecificationZ.ai GLM 5V TurboSpaceXAI Grok 4.5
MakerZ.aixAI
WeightsNo public weights listedNo public weights listed
ReleasedApril 1, 2026July 8, 2026
Context window203K500K
Input $/Mtok$1.20$2.00
Output $/Mtok$4.00$6.00
Coding index28.875.5
Independent measurements behind it12
Cost per solved taskNot computable$0.62
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5V Turbo better than Grok 4.5 for coding?

Pick Grok 4.5 for coding: it scores 75.5 on the Vibe Coding Index against 28.8 for GLM 5V Turbo. Pick GLM 5V Turbo when output tokens cost 1.5x less, or when what matters is Design Arena: agents building Android apps or LMArena Text: English, where it leads.

Which is cheaper, GLM 5V Turbo or Grok 4.5?

GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Grok 4.5 costs $2.00 and $6.00. Cost per solved task is known for Grok 4.5 only.

Which has the bigger context window, GLM 5V Turbo or Grok 4.5?

Grok 4.5, with 500K tokens against 203K.

How many benchmarks is the GLM 5V Turbo vs Grok 4.5 comparison based on?

60 benchmarks have a result for both models as of October 21, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and Grok 4.5's on 2. Where only one model has a result, the page says so instead of naming a winner.

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