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GLM 4.6V vs GPT-5 Mini

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 Mini
GLM 4.6VZ.ai
Coding
No data
Overall
11.2
Output $/M
$0.90
13
GPT-5 MiniOpenAI
Coding
34.2
Overall
20.6
Output $/M
$2.00
25
vs boards won of 38 shared

Decision reading

Only GPT-5 Mini has a coding score, 34.2 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 2.2x less, and where what matters is LMArena Text: hard prompts in English or LMArena Text: science, where it leads.

Model AGLM 4.6VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5 MiniOpenAI34.2/1002 independent benchmarks$0.08 per solved task
Shared results
38
GLM 4.6V only
0
GPT-5 Mini only
60
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 Mini 34.2 from 2 benchmarks.
Widest category
Agentic work, 39.5 points apart on average over 1 shared benchmark.
Widest single gap
IFBench: GLM 4.6V 30.1% against GPT-5 Mini 75.4%, 45.4 points apart on a 0 to 100 scale.
Output price
GLM 4.6V $0.90 against GPT-5 Mini $2.00 per million output tokens, 2.2x apart.
Context window
GLM 4.6V takes 131K tokens, GPT-5 Mini 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-5 MiniTies
Coding04
Intelligence01
Agentic work01
Reasoning16
Math02
Knowledge41
General810
All shared boards1325
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GLM 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
SWE-bench VerifiedNot measured59.8%Only GPT-5 Mini measured
SWE-bench MultilingualNot measured39.7%Only GPT-5 Mini measured
LiveCodeBench (Vals AI)Not measured86.6%Only GPT-5 Mini measured
SWE-bench Verified (Vals AI)Not measured60.8%Only GPT-5 Mini measured
Vibe Code Bench (Vals AI)Not measured14.2%Only GPT-5 Mini measured
LiveCodeBench (Artificial Analysis run)41.1%83.8%GPT-5 Mini
SciCodeNot measured39.0%Only GPT-5 Mini measured
Terminal-Bench Hard (Artificial Analysis run)14.4%33.3%GPT-5 Mini
Terminal-BenchNot measured34.8%Only GPT-5 Mini measured
WeirdMLNot measured52.7%Only GPT-5 Mini measured
LMArena Text: coding13891406GPT-5 Mini
LMArena Text: software and IT13911394GPT-5 Mini
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
AA Intelligence Index11.220.6GPT-5 Mini
Epoch Capabilities IndexNot measured145.3Only GPT-5 Mini measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
τ²-Bench Telecom31.6%71.1%GPT-5 Mini
Vending-Bench 2Not measured-$31Only GPT-5 Mini measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index16
Reasoning benchmarks for GLM 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
GPQA DiamondNot measured80.3%Only GPT-5 Mini measured
MMMU Pro (Vals AI)Not measured78.9%Only GPT-5 Mini measured
GPQA Diamond (Artificial Analysis run)71.9%82.8%GPT-5 Mini
Humanity's Last Exam (Artificial Analysis run)9.6%21.5%GPT-5 Mini
GPQA Diamond (Epoch AI run)Not measured75.0%Only GPT-5 Mini measured
ARC-AGINot measured54.3%Only GPT-5 Mini measured
ARC-AGI-2Not measured4.4%Only GPT-5 Mini measured
Chess puzzlesNot measured24.0%Only GPT-5 Mini measured
Mystery game puzzlesNot measured10.0%Only GPT-5 Mini measured
VPCTNot measured40.2%Only GPT-5 Mini measured
LMArena Text: hard prompts13671380GPT-5 Mini
LMArena Text: expert13711379GPT-5 Mini
LMArena Text: hard prompts in English13911383GLM 4.6V
LMArena Vision: diagrams11821202GPT-5 Mini
LMArena Vision: homework11551210GPT-5 Mini
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 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
AIMENot measured91.5%Only GPT-5 Mini measured
MATH 500 (Vals AI)Not measured94.8%Only GPT-5 Mini measured
MGSM (Vals AI)Not measured92.6%Only GPT-5 Mini measured
AA Math Index85.390.7GPT-5 Mini
AIME 2025 (Artificial Analysis run)85.3%90.7%GPT-5 Mini
OTIS Mock AIMENot measured86.7%Only GPT-5 Mini measured
FrontierMath, tiers 1 to 3Not measured46.7%Only GPT-5 Mini measured
FrontierMath, tier 4Not measured12.2%Only GPT-5 Mini measured
ProofBenchNot measured9.0%Only GPT-5 Mini measured
MATH level 5Not measured97.8%Only GPT-5 Mini measured
LMArena Text: mathNot measured1378Only GPT-5 Mini measured
LMArena Text: mathematical workNot measured1380Only GPT-5 Mini measured
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for GLM 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
MMLU ProNot measured82.2%Only GPT-5 Mini measured
LegalBench (Vals AI)Not measured81.8%Only GPT-5 Mini measured
CaseLaw (Vals AI)Not measured68.5%Only GPT-5 Mini measured
CorpFin (Vals AI)Not measured60.2%Only GPT-5 Mini measured
TaxEval (Vals AI)Not measured75.2%Only GPT-5 Mini measured
MortgageTax (Vals AI)Not measured66.9%Only GPT-5 Mini measured
MedQA (Vals AI)Not measured96.1%Only GPT-5 Mini measured
MedCode (Vals AI)Not measured43.0%Only GPT-5 Mini measured
MMLU Pro (Artificial Analysis run)79.9%83.7%GPT-5 Mini
SimpleQA VerifiedNot measured21.6%Only GPT-5 Mini measured
LMArena Text: science13891371GLM 4.6V
LMArena Text: medicine and healthcare13891380GLM 4.6V
LMArena Text: legal and government13931375GLM 4.6V
LMArena Text: business and finance13591358GLM 4.6V
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 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
Design Arena: websitesNot measured1125Only GPT-5 Mini measured
Design Arena: UI componentsNot measured1106Only GPT-5 Mini measured
Design Arena: game devNot measured1129Only GPT-5 Mini measured
Design Arena: data vizNot measured1130Only GPT-5 Mini measured
Design Arena: 3DNot measured1037Only GPT-5 Mini measured
Design Arena: all code categoriesNot measured1115Only GPT-5 Mini measured
Design Arena: SVGNot measured1091Only GPT-5 Mini measured
Design Arena: ASCII artNot measured1124Only GPT-5 Mini measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index810
General benchmarks for GLM 4.6V and GPT-5 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
SAGE (Vals AI)Not measured43.0%Only GPT-5 Mini measured
MedScribe (Vals AI)Not measured80.6%Only GPT-5 Mini measured
IFBench30.1%75.4%GPT-5 Mini
Long context reasoning (AA-LCR)48.7%72.3%GPT-5 Mini
DTBenchNot measured80.5%Only GPT-5 Mini measured
LMCANot measured34.2%Only GPT-5 Mini measured
Fiction.LiveBenchNot measured69.4%Only GPT-5 Mini measured
Creative writing (Lech Mazur)Not measured83.1%Only GPT-5 Mini measured
LMArena Text13761373GLM 4.6V
LMArena Text: instruction following13501357GPT-5 Mini
LMArena Text: creative writing13471325GLM 4.6V
LMArena Vision11641202GPT-5 Mini
LMArena Text: English13951379GLM 4.6V
LMArena Text: non-English13581363GPT-5 Mini
LMArena Text: Chinese14251386GLM 4.6V
LMArena Text: GermanNot measured1366Only GPT-5 Mini measured
LMArena Text: JapaneseNot measured1341Only GPT-5 Mini measured
LMArena Text: KoreanNot measured1308Only GPT-5 Mini measured
LMArena Text: FrenchNot measured1386Only GPT-5 Mini measured
LMArena Text: SpanishNot measured1354Only GPT-5 Mini measured
LMArena Text: Russian13391362GPT-5 Mini
LMArena Text: PolishNot measured1378Only GPT-5 Mini measured
LMArena Text: multi-turn13591363GPT-5 Mini
LMArena Text: longer queries13571355GLM 4.6V
LMArena Text: writing and language13471344GLM 4.6V
LMArena Text: entertainment and media13431340GLM 4.6V
LMArena Vision: English11791216GPT-5 Mini
LMArena Vision: Chinese12171214GLM 4.6V
LMArena Vision: reading text11711199GPT-5 Mini
LMArena Vision: humorNot measured1205Only GPT-5 Mini measured
LMArena Vision: captioningNot measured1217Only GPT-5 Mini measured
LMArena Vision: recognizing thingsNot measured1226Only GPT-5 Mini measured
LMArena Vision: creative writing11131181GPT-5 Mini
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 Mini
BenchmarkGLM 4.6VGPT-5 MiniLeader
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 Mini$0.0013Fits 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 Mini$0.018Fits 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 Mini$0.070Fits 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 Mini
SpecificationZ.ai GLM 4.6VOpenAI GPT-5 Mini
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 8, 2025August 7, 2025
Context window131K400K
Input $/Mtok$0.30$0.25
Output $/Mtok$0.90$2.00
Coding indexNot benchmarked34.2
Independent measurements behind it02
Cost per solved taskNot computable$0.08
SourceOpenRouter listingOpenRouter listing

Questions

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

Only GPT-5 Mini has a coding score, 34.2 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 2.2x less, and where what matters is LMArena Text: hard prompts in English or LMArena Text: science, where it leads.

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

GLM 4.6V costs $0.30 per million input tokens and $0.90 per million output tokens; GPT-5 Mini costs $0.25 and $2.00. Cost per solved task is known for GPT-5 Mini only.

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

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

How many benchmarks is the GLM 4.6V vs GPT-5 Mini 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 Mini's on 2. Where only one model has a result, the page says so instead of naming a winner.

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