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GLM 4.5V vs o4 Mini

o4 Mini leads GLM 4.5V on the Artificial Analysis Intelligence Index, 16.7 to 7.6, and GLM 4.5V costs 2.4x less per output token ($1.80 vs $4.40 per million). Updated October 21, 2026; 40 benchmarks have a result for both.

Replace GLM 4.5V Replace o4 Mini
GLM 4.5VZ.ai
Coding
No data
Overall
7.6
Output $/M
$1.80
2
o4 MiniOpenAI
Coding
No data
Overall
16.7
Output $/M
$4.40
38
vs boards won of 40 shared

GLM 4.5V or o4 Mini: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GLM 4.5V for output tokens 2.4x cheaper ($1.80 vs $4.40 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model AGLM 4.5VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel Bo4 MiniOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
40
GLM 4.5V only
0
o4 Mini only
54
Like-for-like categories
7 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, o4 Mini not benchmarked.
Widest category
Agentic work, 33.0 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): GLM 4.5V 0.0% against o4 Mini 61.0%, 61.0 points apart on a 0 to 100 scale.
Output price
GLM 4.5V $1.80 against o4 Mini $4.40 per million output tokens, 2.4x apart.
Context window
GLM 4.5V takes 66K tokens, o4 Mini 200K.

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 4.5VBarso4 MiniTies
Coding04
Intelligence01
Agentic work01
Reasoning16
Math04
Knowledge05
General117
All shared boards238
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GLM 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
Aider polyglotNot measured72.0%Only o4 Mini measured
SWE-bench VerifiedNot measured64.6%Only o4 Mini measured
SWE-bench MultimodalNot measured33.9%Only o4 Mini measured
LiveCodeBench (Vals AI)Not measured82.2%Only o4 Mini measured
LiveCodeBench (Artificial Analysis run)60.4%85.9%o4 Mini
Terminal-Bench Hard (Artificial Analysis run)6.8%15.2%o4 Mini
GSO-BenchNot measured3.6%Only o4 Mini measured
WeirdMLNot measured52.6%Only o4 Mini measured
LMArena Text: coding13471368o4 Mini
LMArena Text: software and IT13531367o4 Mini
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
AA Intelligence Index7.616.7o4 Mini
Epoch Capabilities IndexNot measured145.5Only o4 Mini measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
τ²-Bench Telecom22.5%55.6%o4 Mini
METR time horizonsNot measured63.9%Only o4 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 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
GPQA DiamondNot measured74.5%Only o4 Mini measured
MMMU Pro (Vals AI)Not measured79.7%Only o4 Mini measured
GPQA Diamond (Artificial Analysis run)68.4%78.4%o4 Mini
Humanity's Last Exam (Artificial Analysis run)6.3%16.5%o4 Mini
GPQA Diamond (Epoch AI run)Not measured79.6%Only o4 Mini measured
ARC-AGINot measured58.7%Only o4 Mini measured
ARC-AGI-2Not measured6.1%Only o4 Mini measured
SimpleBenchNot measured38.7%Only o4 Mini measured
Chess puzzlesNot measured22.0%Only o4 Mini measured
Mystery game puzzlesNot measured5.0%Only o4 Mini measured
VPCTNot measured57.5%Only o4 Mini measured
LMArena Text: hard prompts13351351o4 Mini
LMArena Text: expert13531343GLM 4.5V
LMArena Text: hard prompts in English13571366o4 Mini
LMArena Vision: diagrams11511197o4 Mini
LMArena Vision: homework11631234o4 Mini
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GLM 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
AIMENot measured83.7%Only o4 Mini measured
MATH 500 (Vals AI)Not measured94.2%Only o4 Mini measured
MGSM (Vals AI)Not measured93.4%Only o4 Mini measured
AA Math Index73.090.7o4 Mini
AIME 2025 (Artificial Analysis run)73.0%90.7%o4 Mini
OTIS Mock AIMENot measured81.7%Only o4 Mini measured
FrontierMath, tiers 1 to 3Not measured36.1%Only o4 Mini measured
FrontierMath, tier 4Not measured4.9%Only o4 Mini measured
MATH level 5Not measured97.8%Only o4 Mini measured
LMArena Text: math13541389o4 Mini
LMArena Text: mathematical work13361379o4 Mini
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GLM 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
MMLU ProNot measured80.6%Only o4 Mini measured
LegalBench (Vals AI)Not measured79.2%Only o4 Mini measured
CorpFin (Vals AI)Not measured59.0%Only o4 Mini measured
TaxEval (Vals AI)Not measured74.8%Only o4 Mini measured
MortgageTax (Vals AI)Not measured64.8%Only o4 Mini measured
MedQA (Vals AI)Not measured96.0%Only o4 Mini measured
MedCode (Vals AI)Not measured33.8%Only o4 Mini measured
MMLU Pro (Artificial Analysis run)78.8%83.2%o4 Mini
SimpleQA VerifiedNot measured19.6%Only o4 Mini measured
GeoBenchNot measured64.0%Only o4 Mini measured
LMArena Text: science13301354o4 Mini
LMArena Text: medicine and healthcare13491361o4 Mini
LMArena Text: legal and government13381350o4 Mini
LMArena Text: business and finance13091325o4 Mini
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GLM 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
Design Arena: websitesNot measured985Only o4 Mini measured
Design Arena: UI componentsNot measured983Only o4 Mini measured
Design Arena: game devNot measured1003Only o4 Mini measured
Design Arena: data vizNot measured990Only o4 Mini measured
Design Arena: 3DNot measured854Only o4 Mini measured
Design Arena: all code categoriesNot measured976Only o4 Mini measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index117
General benchmarks for GLM 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 MiniLeader
SAGE (Vals AI)Not measured41.1%Only o4 Mini measured
MedScribe (Vals AI)Not measured69.1%Only o4 Mini measured
IFBench34.2%68.7%o4 Mini
Long context reasoning (AA-LCR)0.0%61.0%o4 Mini
DTBenchNot measured77.6%Only o4 Mini measured
LMCANot measured26.5%Only o4 Mini measured
Fiction.LiveBenchNot measured77.8%Only o4 Mini measured
Creative writing (Lech Mazur)Not measured75.0%Only o4 Mini measured
LMArena Text13331353o4 Mini
LMArena Text: instruction following13111320o4 Mini
LMArena Text: creative writing12941294GLM 4.5V
LMArena Vision11541194o4 Mini
LMArena Text: English13621367o4 Mini
LMArena Text: non-English13031337o4 Mini
LMArena Text: Chinese13371354o4 Mini
LMArena Text: GermanNot measured1336Only o4 Mini measured
LMArena Text: JapaneseNot measured1308Only o4 Mini measured
LMArena Text: KoreanNot measured1312Only o4 Mini measured
LMArena Text: FrenchNot measured1364Only o4 Mini measured
LMArena Text: Spanish13361346o4 Mini
LMArena Text: Russian12981334o4 Mini
LMArena Text: Polish13021358o4 Mini
LMArena Text: multi-turn13331350o4 Mini
LMArena Text: longer queries13051315o4 Mini
LMArena Text: writing and language13021316o4 Mini
LMArena Text: entertainment and media13031308o4 Mini
LMArena Vision: English11831200o4 Mini
LMArena Vision: ChineseNot measured1218Only o4 Mini measured
LMArena Vision: reading text11511197o4 Mini
LMArena Vision: humorNot measured1199Only o4 Mini measured
LMArena Vision: captioningNot measured1204Only o4 Mini measured
LMArena Vision: recognizing thingsNot measured1218Only o4 Mini measured
LMArena Vision: creative writingNot measured1166Only o4 Mini measured
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 4.5V and o4 Mini
BenchmarkGLM 4.5Vo4 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 4.5V$0.0015Fits in one request
o4 Mini$0.0033Fits in one request

GLM 4.5V costs less

Repository review

50K input + 3K output tokens

GLM 4.5V$0.035Fits in one request
o4 Mini$0.068Fits in one request

GLM 4.5V costs less

Agent loop

200K input + 10K output tokens

GLM 4.5V$0.138Exceeds the context window
o4 Mini$0.264Exceeds the context window

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 o4 Mini
SpecificationZ.ai GLM 4.5VOpenAI o4 Mini
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedAugust 11, 2025April 16, 2025
Context window66K200K
Input $/Mtok$0.60$1.10
Output $/Mtok$1.80$4.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5V better than o4 Mini for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5V for output tokens 2.4x cheaper ($1.80 vs $4.40 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, GLM 4.5V or o4 Mini?

GLM 4.5V costs $0.60 per million input tokens and $1.80 per million output tokens; o4 Mini costs $1.10 and $4.40. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.5V or o4 Mini?

o4 Mini, with 200K tokens against 66K.

How many benchmarks is the GLM 4.5V vs o4 Mini comparison based on?

40 benchmarks have a result for both models as of October 21, 2026. GLM 4.5V's coding index rests on 0 independent benchmarks and o4 Mini's on 0. Where only one model has a result, the page says so instead of naming a winner.

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