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GLM 4.6V vs GPT-5

Updated October 21, 2026. 38 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.6V Replace GPT-5
GLM 4.6VZ.ai
Coding
No data
Overall
11.2
Output $/M
$0.90
1
GPT-5OpenAI
Coding
38.8
Overall
23.0
Output $/M
$10.00
37
vs boards won of 38 shared

Decision reading

Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; GLM 4.6V has none, so the two cannot be ranked on coding.

GLM 4.6V has the edge where output tokens cost 11.1x less, and where the benchmark that matters is LMArena Text: Chinese, where it leads.

Model AGLM 4.6VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5OpenAI38.8/1003 independent benchmarks$0.39 per solved task
Shared results
38
GLM 4.6V only
0
GPT-5 only
71
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 4.6V not benchmarked, GPT-5 38.8 from 3 benchmarks.
Widest category
Agentic work, 55.0 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.6V 31.6% against GPT-5 86.5%, 55.0 points apart on a 0 to 100 scale.
Output price
GLM 4.6V $0.90 against GPT-5 $10.00 per million output tokens, 11.1x apart.
Context window
GLM 4.6V takes 131K tokens, GPT-5 400K.

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 4.6VBarsGPT-5Ties
Coding04
Intelligence01
Agentic work01
Reasoning07
Math02
Knowledge05
General117
All shared boards137
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
Aider polyglotNot measured88.0%Only GPT-5 measured
SWE-bench VerifiedNot measured74.4%Only GPT-5 measured
LMArena WebDevNot measured1418Only GPT-5 measured
AA Coding IndexNot measured37.8Only GPT-5 measured
LiveCodeBench (Vals AI)Not measured85.9%Only GPT-5 measured
SWE-bench Verified (Vals AI)Not measured69.0%Only GPT-5 measured
Vibe Code Bench (Vals AI)Not measured20.1%Only GPT-5 measured
LiveCodeBench (Artificial Analysis run)41.1%84.6%GPT-5
Terminal-Bench Hard (Artificial Analysis run)14.4%37.9%GPT-5
Terminal-BenchNot measured49.6%Only GPT-5 measured
GSO-BenchNot measured6.9%Only GPT-5 measured
WeirdMLNot measured60.7%Only GPT-5 measured
ALE-BenchNot measured807.6Only GPT-5 measured
LMArena Text: coding13891436GPT-5
LMArena Text: software and IT13911420GPT-5
LMArena WebDev: HTMLNot measured1427Only GPT-5 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
AA Intelligence Index11.223.0GPT-5
Epoch Capabilities IndexNot measured150.0Only GPT-5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
τ²-Bench Telecom31.6%86.5%GPT-5
METR time horizonsNot measured69.6%Only GPT-5 measured
Remote Labor IndexNot measured1.7%Only GPT-5 measured
GDPvalNot measured34.8%Only GPT-5 measured
BALROGNot measured32.8%Only GPT-5 measured
DeepResearch BenchNot measured49.6%Only GPT-5 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
GPQA DiamondNot measured85.6%Only GPT-5 measured
MMMU Pro (Vals AI)Not measured81.5%Only GPT-5 measured
GPQA Diamond (Artificial Analysis run)71.9%85.4%GPT-5
Humanity's Last Exam (Artificial Analysis run)9.6%28.5%GPT-5
GPQA Diamond (Epoch AI run)Not measured86.2%Only GPT-5 measured
ARC-AGINot measured65.7%Only GPT-5 measured
ARC-AGI-2Not measured9.9%Only GPT-5 measured
SimpleBenchNot measured56.7%Only GPT-5 measured
Chess puzzlesNot measured36.0%Only GPT-5 measured
Mystery game puzzlesNot measured23.0%Only GPT-5 measured
EBR-benchNot measured12.7%Only GPT-5 measured
VPCTNot measured66.0%Only GPT-5 measured
LMArena Text: hard prompts13671415GPT-5
LMArena Text: expert13711419GPT-5
LMArena Text: hard prompts in English13911419GPT-5
LMArena Vision: diagrams11821252GPT-5
LMArena Vision: homework11551278GPT-5
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
AIMENot measured93.4%Only GPT-5 measured
MATH 500 (Vals AI)Not measured96.0%Only GPT-5 measured
MGSM (Vals AI)Not measured92.8%Only GPT-5 measured
AA Math Index85.394.3GPT-5
AIME 2025 (Artificial Analysis run)85.3%94.3%GPT-5
OTIS Mock AIMENot measured91.4%Only GPT-5 measured
FrontierMath, tiers 1 to 3Not measured55.4%Only GPT-5 measured
FrontierMath, tier 4Not measured22.0%Only GPT-5 measured
ProofBenchNot measured18.0%Only GPT-5 measured
MATH level 5Not measured98.1%Only GPT-5 measured
LMArena Text: mathNot measured1407Only GPT-5 measured
LMArena Text: mathematical workNot measured1405Only GPT-5 measured
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
MMLU ProNot measured86.5%Only GPT-5 measured
LegalBench (Vals AI)Not measured86.0%Only GPT-5 measured
CaseLaw (Vals AI)Not measured66.5%Only GPT-5 measured
CorpFin (Vals AI)Not measured61.1%Only GPT-5 measured
TaxEval (Vals AI)Not measured73.4%Only GPT-5 measured
MortgageTax (Vals AI)Not measured65.5%Only GPT-5 measured
MedQA (Vals AI)Not measured96.3%Only GPT-5 measured
MedCode (Vals AI)Not measured49.6%Only GPT-5 measured
MMLU Pro (Artificial Analysis run)79.9%87.1%GPT-5
SimpleQA VerifiedNot measured50.1%Only GPT-5 measured
GeoBenchNot measured81.0%Only GPT-5 measured
LMArena Text: science13891416GPT-5
LMArena Text: medicine and healthcare13891413GPT-5
LMArena Text: legal and government13931431GPT-5
LMArena Text: business and finance13591400GPT-5
Neither model has a result on the other 2 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
Design Arena: websitesNot measured1185Only GPT-5 measured
Design Arena: UI componentsNot measured1180Only GPT-5 measured
Design Arena: game devNot measured1185Only GPT-5 measured
Design Arena: data vizNot measured1221Only GPT-5 measured
Design Arena: 3DNot measured1056Only GPT-5 measured
Design Arena: all code categoriesNot measured1168Only GPT-5 measured
Design Arena: SVGNot measured1189Only GPT-5 measured
Design Arena: ASCII artNot measured1140Only GPT-5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index117
General benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-5Leader
SAGE (Vals AI)Not measured43.7%Only GPT-5 measured
MedScribe (Vals AI)Not measured83.7%Only GPT-5 measured
IFBench30.1%73.1%GPT-5
Long context reasoning (AA-LCR)48.7%78.2%GPT-5
DTBenchNot measured90.7%Only GPT-5 measured
LMCANot measured40.0%Only GPT-5 measured
Fiction.LiveBenchNot measured97.2%Only GPT-5 measured
Creative writing (Lech Mazur)Not measured86.0%Only GPT-5 measured
LMArena Text13761406GPT-5
LMArena Text: instruction following13501388GPT-5
LMArena Text: creative writing13471365GPT-5
LMArena Vision11641232GPT-5
LMArena Text: English13951409GPT-5
LMArena Text: non-English13581397GPT-5
LMArena Text: Chinese14251422GLM 4.6V
LMArena Text: GermanNot measured1416Only GPT-5 measured
LMArena Text: JapaneseNot measured1409Only GPT-5 measured
LMArena Text: KoreanNot measured1360Only GPT-5 measured
LMArena Text: FrenchNot measured1409Only GPT-5 measured
LMArena Text: SpanishNot measured1399Only GPT-5 measured
LMArena Text: Russian13391407GPT-5
LMArena Text: PolishNot measured1431Only GPT-5 measured
LMArena Text: multi-turn13591426GPT-5
LMArena Text: longer queries13571399GPT-5
LMArena Text: writing and language13471384GPT-5
LMArena Text: entertainment and media13431379GPT-5
LMArena Vision: English11791231GPT-5
LMArena Vision: Chinese12171267GPT-5
LMArena Vision: reading text11711246GPT-5
LMArena Vision: humorNot measured1219Only GPT-5 measured
LMArena Vision: captioningNot measured1212Only GPT-5 measured
LMArena Vision: recognizing thingsNot measured1263Only GPT-5 measured
LMArena Vision: creative writing11131210GPT-5
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.6V and GPT-5
BenchmarkGLM 4.6VGPT-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 4.6V$0.0008Fits in one request
GPT-5$0.0063Fits in one request

GLM 4.6V costs less

Repository review

50K input + 3K output tokens

GLM 4.6V$0.018Fits in one request
GPT-5$0.092Fits in one request

GLM 4.6V costs less

Agent loop

200K input + 10K output tokens

GLM 4.6V$0.069Exceeds the context window
GPT-5$0.350Fits in one request

GLM 4.6V 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 4.6V and GPT-5
SpecificationZ.ai GLM 4.6VOpenAI GPT-5
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 8, 2025August 7, 2025
Context window131K400K
Input $/Mtok$0.30$1.25
Output $/Mtok$0.90$10.00
Coding indexNot benchmarked38.8
Independent measurements behind it03
Cost per solved taskNot computable$0.39
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.6V better than GPT-5 for coding?

Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; GLM 4.6V has none, so the two cannot be ranked on coding. GLM 4.6V has the edge where output tokens cost 11.1x less, and where the benchmark that matters is LMArena Text: Chinese, where it leads.

Which is cheaper, GLM 4.6V or GPT-5?

GLM 4.6V costs $0.30 per million input tokens and $0.90 per million output tokens; GPT-5 costs $1.25 and $10.00. Cost per solved task is known for GPT-5 only.

Which has the bigger context window, GLM 4.6V or GPT-5?

GPT-5, with 400K tokens against 131K.

How many benchmarks is the GLM 4.6V vs GPT-5 comparison based on?

38 benchmarks have a result for both models as of October 21, 2026. GLM 4.6V's coding index rests on 0 independent benchmarks and GPT-5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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