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GLM 4.7 Flash vs GPT-5.4 Mini

Updated October 21, 2026. 36 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.7 Flash Replace GPT-5.4 Mini
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
1
GPT-5.4 MiniOpenAI
Coding
35.8
Overall
24.1
Output $/M
$4.50
35
vs boards won of 36 shared

Decision reading

Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.

GLM 4.7 Flash has the edge where output tokens cost 11.3x less, and where the benchmark that matters is τ²-Bench Telecom, where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5.4 MiniOpenAI35.8/1005 independent benchmarks$0.70 per solved task
Shared results
36
GLM 4.7 Flash only
7
GPT-5.4 Mini only
52
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 4.7 Flash not benchmarked, GPT-5.4 Mini 35.8 from 5 benchmarks.
Widest category
Reasoning, 18.2 points apart on average over 6 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): GLM 4.7 Flash 41.7% against GPT-5.4 Mini 77.0%, 35.3 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against GPT-5.4 Mini $4.50 per million output tokens, 11.3x apart.
Context window
GLM 4.7 Flash takes 200K tokens, GPT-5.4 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 4.7 FlashBarsGPT-5.4 MiniTies
Coding03
Intelligence01
Agentic work10
Reasoning06
Math03
Knowledge04
General018
All shared boards135
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
LMArena WebDevNot measured1397Only GPT-5.4 Mini measured
AA Coding IndexNot measured56.1Only GPT-5.4 Mini measured
LiveCodeBench (Vals AI)Not measured81.5%Only GPT-5.4 Mini measured
SWE-bench Verified (Vals AI)Not measured73.0%Only GPT-5.4 Mini measured
Terminal-Bench 4 (Vals AI)Not measured2.5%Only GPT-5.4 Mini measured
Vibe Code Bench (Vals AI)Not measured48.0%Only GPT-5.4 Mini measured
Code migration (Vals AI)Not measured12.9%Only GPT-5.4 Mini measured
ProgramBench (Vals AI)Not measured0.0%Only GPT-5.4 Mini measured
Terminal-Bench 2.1 (Vals AI)Not measured54.7%Only GPT-5.4 Mini measured
SciCodeNot measured52.1%Only GPT-5.4 Mini measured
Terminal-Bench Hard (Artificial Analysis run)22.0%52.3%GPT-5.4 Mini
FrontierCodeNot measured27.0%Only GPT-5.4 Mini measured
WeirdMLNot measured60.3%Only GPT-5.4 Mini measured
ALE-BenchNot measured1188.6Only GPT-5.4 Mini measured
LMArena Text: coding13821438GPT-5.4 Mini
LMArena Text: software and IT13891436GPT-5.4 Mini
LMArena WebDev: ReactNot measured1386Only GPT-5.4 Mini measured
LMArena WebDev: HTMLNot measured1419Only GPT-5.4 Mini measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
AA Intelligence Index14.924.1GPT-5.4 Mini
Epoch Capabilities IndexNot measured148.7Only GPT-5.4 Mini measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
AA Agentic IndexNot measured17.9Only GPT-5.4 Mini measured
Finance Agent (Vals AI)Not measured45.4%Only GPT-5.4 Mini measured
Tax Agent Bench (Vals AI)Not measured8.8%Only GPT-5.4 Mini measured
Legal Research Bench (Vals AI)Not measured12.5%Only GPT-5.4 Mini measured
Excel Modeling Benchmark (Vals AI)Not measured45.4%Only GPT-5.4 Mini measured
τ²-Bench Telecom98.8%83.3%GLM 4.7 Flash
DeepResearch BenchNot measured36.3%Only GPT-5.4 Mini measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
GPQA DiamondNot measured83.1%Only GPT-5.4 Mini measured
MMMU Pro (Vals AI)Not measured79.3%Only GPT-5.4 Mini measured
GPQA Diamond (Artificial Analysis run)58.1%87.5%GPT-5.4 Mini
Humanity's Last Exam (Artificial Analysis run)7.6%28.1%GPT-5.4 Mini
GPQA Diamond (Epoch AI run)60.5%86.9%GPT-5.4 Mini
ARC-AGINot measured63.7%Only GPT-5.4 Mini measured
ARC-AGI-2Not measured18.9%Only GPT-5.4 Mini measured
Chess puzzlesNot measured23.0%Only GPT-5.4 Mini measured
Mystery game puzzlesNot measured11.0%Only GPT-5.4 Mini measured
LMArena Text: hard prompts13561424GPT-5.4 Mini
LMArena Text: expert13571435GPT-5.4 Mini
LMArena Text: hard prompts in English13691420GPT-5.4 Mini
LMArena Vision: diagramsNot measured1266Only GPT-5.4 Mini measured
LMArena Vision: homeworkNot measured1285Only GPT-5.4 Mini measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
AIMENot measured95.6%Only GPT-5.4 Mini measured
OTIS Mock AIME58.3%88.9%GPT-5.4 Mini
FrontierMath, tiers 1 to 3Not measured51.2%Only GPT-5.4 Mini measured
FrontierMath, tier 4Not measured9.8%Only GPT-5.4 Mini measured
ProofBenchNot measured21.0%Only GPT-5.4 Mini measured
LMArena Text: math13551418GPT-5.4 Mini
LMArena Text: mathematical work13691429GPT-5.4 Mini
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
MMLU ProNot measured84.5%Only GPT-5.4 Mini measured
CaseLaw (Vals AI)Not measured51.7%Only GPT-5.4 Mini measured
CorpFin (Vals AI)Not measured60.9%Only GPT-5.4 Mini measured
TaxEval (Vals AI)Not measured71.2%Only GPT-5.4 Mini measured
MortgageTax (Vals AI)Not measured63.5%Only GPT-5.4 Mini measured
SimpleQA VerifiedNot measured29.4%Only GPT-5.4 Mini measured
LMArena Text: science13581417GPT-5.4 Mini
LMArena Text: medicine and healthcare13431395GPT-5.4 Mini
LMArena Text: legal and government13571414GPT-5.4 Mini
LMArena Text: business and finance13431418GPT-5.4 Mini
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
Design Arena: websites1194Not measuredOnly GLM 4.7 Flash measured
Design Arena: UI components1208Not measuredOnly GLM 4.7 Flash measured
Design Arena: game dev1135Not measuredOnly GLM 4.7 Flash measured
Design Arena: data viz1123Not measuredOnly GLM 4.7 Flash measured
Design Arena: 3D1121Not measuredOnly GLM 4.7 Flash measured
Design Arena: all code categories1178Not measuredOnly GLM 4.7 Flash measured
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 index018
General benchmarks for GLM 4.7 Flash and GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 MiniLeader
SAGE (Vals AI)Not measured50.8%Only GPT-5.4 Mini measured
Vals Multimodal IndexNot measured54.2%Only GPT-5.4 Mini measured
IFBench60.8%73.3%GPT-5.4 Mini
Long context reasoning (AA-LCR)41.7%77.0%GPT-5.4 Mini
DTBenchNot measured80.0%Only GPT-5.4 Mini measured
LMCANot measured40.8%Only GPT-5.4 Mini measured
LMArena Text13511412GPT-5.4 Mini
LMArena Text: instruction following13271405GPT-5.4 Mini
LMArena Text: creative writing12961370GPT-5.4 Mini
LMArena VisionNot measured1245Only GPT-5.4 Mini measured
LMArena Text: English13731412GPT-5.4 Mini
LMArena Text: non-English13301405GPT-5.4 Mini
LMArena Text: Chinese14031446GPT-5.4 Mini
LMArena Text: German13361408GPT-5.4 Mini
LMArena Text: JapaneseNot measured1375Only GPT-5.4 Mini measured
LMArena Text: Korean12831370GPT-5.4 Mini
LMArena Text: French13321441GPT-5.4 Mini
LMArena Text: Spanish13501405GPT-5.4 Mini
LMArena Text: Russian13331417GPT-5.4 Mini
LMArena Text: Polish12911415GPT-5.4 Mini
LMArena Text: multi-turn13421429GPT-5.4 Mini
LMArena Text: longer queries13451408GPT-5.4 Mini
LMArena Text: writing and language13201393GPT-5.4 Mini
LMArena Text: entertainment and media13041373GPT-5.4 Mini
LMArena Vision: EnglishNot measured1244Only GPT-5.4 Mini measured
LMArena Vision: ChineseNot measured1286Only GPT-5.4 Mini measured
LMArena Vision: reading textNot measured1253Only GPT-5.4 Mini measured
LMArena Vision: humorNot measured1235Only GPT-5.4 Mini measured
LMArena Vision: recognizing thingsNot measured1218Only GPT-5.4 Mini measured
LMArena Vision: creative writingNot measured1222Only GPT-5.4 Mini measured
Neither model has a result on the other 16 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 GPT-5.4 Mini
BenchmarkGLM 4.7 FlashGPT-5.4 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
GPT-5.4 Mini$0.0030Fits 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
GPT-5.4 Mini$0.051Fits 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
GPT-5.4 Mini$0.195Fits in one request

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 GPT-5.4 Mini
SpecificationZ.ai GLM 4.7 FlashOpenAI GPT-5.4 Mini
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJanuary 19, 2026March 17, 2026
Context window200K400K
Input $/Mtok$0.0653$0.75
Output $/Mtok$0.40$4.50
Coding indexNot benchmarked35.8
Independent measurements behind it05
Cost per solved taskNot computable$0.70
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than GPT-5.4 Mini for coding?

Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. GLM 4.7 Flash has the edge where output tokens cost 11.3x less, and where the benchmark that matters is τ²-Bench Telecom, where it leads.

Which is cheaper, GLM 4.7 Flash or GPT-5.4 Mini?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; GPT-5.4 Mini costs $0.75 and $4.50. Cost per solved task is known for GPT-5.4 Mini only.

Which has the bigger context window, GLM 4.7 Flash or GPT-5.4 Mini?

GPT-5.4 Mini, with 400K tokens against 200K.

How many benchmarks is the GLM 4.7 Flash vs GPT-5.4 Mini comparison based on?

36 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 GPT-5.4 Mini's on 5. Where only one model has a result, the page says so instead of naming a winner.

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