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GLM 4.7 Flash vs o4 Mini

o4 Mini leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 16.7 to 14.9, and GLM 4.7 Flash costs 11.0x less per output token ($0.40 vs $4.40 per million). Updated October 21, 2026; 42 benchmarks have a result for both.

Replace GLM 4.7 Flash Replace o4 Mini
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
24
o4 MiniOpenAI
Coding
No data
Overall
43.0
Output $/M
$4.40
18
vs boards won of 42 shared

GLM 4.7 Flash or o4 Mini: which to pick

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

Pick GLM 4.7 Flash for output tokens 11.0x cheaper ($0.40 vs $4.40 per million) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel Bo4 MiniOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
42
GLM 4.7 Flash only
1
o4 Mini only
56
Like-for-like categories
8 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 4.7 Flash not benchmarked, o4 Mini not benchmarked.
Widest category
Agentic work, 43.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.7 Flash 98.8% against o4 Mini 55.6%, 43.3 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against o4 Mini $4.40 per million output tokens, 11.0x apart.
Context window
Both take 200K tokens.

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 4.7 FlashBarso4 MiniTies
Coding30
Intelligence01
Agentic work10
Reasoning33
Math03
Knowledge31
Web design60
General810
All shared boards2418
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 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)Not measured85.9%Only o4 Mini measured
Terminal-Bench Hard (Artificial Analysis run)22.0%15.2%GLM 4.7 Flash
GSO-BenchNot measured3.6%Only o4 Mini measured
WeirdMLNot measured52.6%Only o4 Mini measured
LMArena Text: coding13821368GLM 4.7 Flash
LMArena Text: software and IT13891367GLM 4.7 Flash
SciCodeNot measured10.8%Only o4 Mini measured
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 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 MiniLeader
AA Intelligence Index14.916.7o4 Mini
Epoch Capabilities IndexNot measured145.5Only o4 Mini measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 MiniLeader
τ²-Bench Telecom98.8%55.6%GLM 4.7 Flash
METR time horizonsNot measured63.9%Only o4 Mini measured
Berkeley Function Calling Leaderboard (BFCL)Not measured53.2%Only o4 Mini measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
Reasoning benchmarks for GLM 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 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)58.1%78.4%o4 Mini
Humanity's Last Exam (Artificial Analysis run)7.6%16.5%o4 Mini
GPQA Diamond (Epoch AI run)60.5%79.6%o4 Mini
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 prompts13561351GLM 4.7 Flash
LMArena Text: expert13571343GLM 4.7 Flash
LMArena Text: hard prompts in English13691366GLM 4.7 Flash
LMArena Vision: diagramsNot measured1197Only o4 Mini measured
LMArena Vision: homeworkNot measured1234Only o4 Mini measured
Kagi LLM BenchmarkNot measured67.6%Only o4 Mini measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GLM 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 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 IndexNot measured90.7Only o4 Mini measured
AIME 2025 (Artificial Analysis run)Not measured90.7%Only o4 Mini measured
OTIS Mock AIME58.3%81.7%o4 Mini
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: math13551389o4 Mini
LMArena Text: mathematical work13691379o4 Mini
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
Knowledge benchmarks for GLM 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 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)Not measured83.2%Only o4 Mini measured
SimpleQA VerifiedNot measured19.6%Only o4 Mini measured
GeoBenchNot measured64.0%Only o4 Mini measured
LMArena Text: science13581354GLM 4.7 Flash
LMArena Text: medicine and healthcare13431361o4 Mini
LMArena Text: legal and government13571350GLM 4.7 Flash
LMArena Text: business and finance13431325GLM 4.7 Flash
FACTS Benchmark SuiteNot measured28.1%Only o4 Mini measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for GLM 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 MiniLeader
Design Arena: websites1194985GLM 4.7 Flash
Design Arena: UI components1208983GLM 4.7 Flash
Design Arena: game dev11351003GLM 4.7 Flash
Design Arena: data viz1123990GLM 4.7 Flash
Design Arena: 3D1121854GLM 4.7 Flash
Design Arena: all code categories1178976GLM 4.7 Flash
Design Arena: SVG1038Not measuredOnly GLM 4.7 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index810
General benchmarks for GLM 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 MiniLeader
SAGE (Vals AI)Not measured41.1%Only o4 Mini measured
MedScribe (Vals AI)Not measured69.1%Only o4 Mini measured
IFBench60.8%68.7%o4 Mini
Long context reasoning (AA-LCR)41.7%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 Text13511353o4 Mini
LMArena Text: instruction following13271320GLM 4.7 Flash
LMArena Text: creative writing12961294GLM 4.7 Flash
LMArena VisionNot measured1194Only o4 Mini measured
LMArena Text: English13731367GLM 4.7 Flash
LMArena Text: non-English13301337o4 Mini
LMArena Text: Chinese14031354GLM 4.7 Flash
LMArena Text: German13361336GLM 4.7 Flash
LMArena Text: JapaneseNot measured1308Only o4 Mini measured
LMArena Text: Korean12831312o4 Mini
LMArena Text: French13321364o4 Mini
LMArena Text: Spanish13501346GLM 4.7 Flash
LMArena Text: Russian13331334o4 Mini
LMArena Text: Polish12911358o4 Mini
LMArena Text: multi-turn13421350o4 Mini
LMArena Text: longer queries13451315GLM 4.7 Flash
LMArena Text: writing and language13201316GLM 4.7 Flash
LMArena Text: entertainment and media13041308o4 Mini
LMArena Vision: EnglishNot measured1200Only o4 Mini measured
LMArena Vision: ChineseNot measured1218Only o4 Mini measured
LMArena Vision: reading textNot measured1197Only o4 Mini measured
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 4.7 Flash and o4 Mini
BenchmarkGLM 4.7 Flasho4 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 4.7 Flash$0.0003Fits in one request
o4 Mini$0.0033Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

GLM 4.7 Flash$0.0045Fits in one request
o4 Mini$0.068Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 4.7 Flash$0.017Exceeds the context window
o4 Mini$0.264Exceeds the context window

GLM 4.7 Flash 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 4.7 Flash and o4 Mini
SpecificationZ.ai GLM 4.7 FlashOpenAI o4 Mini
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJanuary 19, 2026April 16, 2025
Context window200K200K
Input $/Mtok$0.0653$1.10
Output $/Mtok$0.40$4.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than o4 Mini for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 11.0x cheaper ($0.40 vs $4.40 per million) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, GLM 4.7 Flash or o4 Mini?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 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 4.7 Flash or o4 Mini?

Neither: both take 200K tokens.

How many benchmarks is the GLM 4.7 Flash vs o4 Mini comparison based on?

42 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 Flash'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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