Enter opens the highlighted result. Esc closes.

GLM 4.7 Flash vs GPT-5.4 Nano

GPT-5.4 Nano leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 20.7 to 14.9, and GLM 4.7 Flash costs 3.1x less per output token ($0.40 vs $1.25 per million). Updated October 22, 2026; 36 benchmarks have a result for both.

Replace GLM 4.7 Flash Replace GPT-5.4 Nano
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
2
GPT-5.4 NanoOpenAI
Coding
44.8
Overall
45.7
Output $/M
$1.25
34
vs boards won of 36 shared

GLM 4.7 Flash or GPT-5.4 Nano: which to pick

Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.

Pick GLM 4.7 Flash for output tokens 3.1x cheaper ($0.40 vs $1.25 per million) and work measured by τ²-Bench Telecom or LMArena Text: Chinese, where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5.4 NanoOpenAI44.8/1002 independent benchmarks$0.14 per solved task
Shared results
36
GLM 4.7 Flash only
7
GPT-5.4 Nano only
49
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 4.7 Flash not benchmarked, GPT-5.4 Nano 44.8 from 2 benchmarks.
Widest category
Agentic work, 22.8 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): GLM 4.7 Flash 41.7% against GPT-5.4 Nano 76.7%, 35.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against GPT-5.4 Nano $1.25 per million output tokens, 3.1x apart.
Context window
GLM 4.7 Flash takes 200K tokens, GPT-5.4 Nano 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 NanoTies
Coding03
Intelligence01
Agentic work10
Reasoning06
Math03
Knowledge04
General117
All shared boards234
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.7 Flash and GPT-5.4 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
AA Coding IndexNot measured56.1Only GPT-5.4 Nano measured
LiveCodeBench (Vals AI)Not measured84.0%Only GPT-5.4 Nano measured
SWE-bench Verified (Vals AI)Not measured69.8%Only GPT-5.4 Nano measured
Vibe Code Bench (Vals AI)Not measured26.1%Only GPT-5.4 Nano measured
Code migration (Vals AI)Not measured14.5%Only GPT-5.4 Nano measured
Terminal-Bench 2.1 (Vals AI)Not measured41.6%Only GPT-5.4 Nano measured
SciCodeNot measured47.2%Only GPT-5.4 Nano measured
Terminal-Bench Hard (Artificial Analysis run)22.0%42.4%GPT-5.4 Nano
WeirdMLNot measured49.2%Only GPT-5.4 Nano measured
ALE-BenchNot measured1004.5Only GPT-5.4 Nano measured
LMArena Text: coding13821404GPT-5.4 Nano
LMArena Text: software and IT13891402GPT-5.4 Nano
Neither model has a result on the other 27 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 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
AA Intelligence Index14.920.7GPT-5.4 Nano
Epoch Capabilities IndexNot measured146.0Only GPT-5.4 Nano 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 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
AA Agentic IndexNot measured16.0Only GPT-5.4 Nano measured
Finance Agent (Vals AI)Not measured38.2%Only GPT-5.4 Nano measured
Tax Agent Bench (Vals AI)Not measured5.0%Only GPT-5.4 Nano measured
Legal Research Bench (Vals AI)Not measured6.3%Only GPT-5.4 Nano measured
Excel Modeling Benchmark (Vals AI)Not measured44.8%Only GPT-5.4 Nano measured
τ²-Bench Telecom98.8%76.0%GLM 4.7 Flash
Neither model has a result on the other 35 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 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
GPQA DiamondNot measured77.5%Only GPT-5.4 Nano measured
MMMU Pro (Vals AI)Not measured73.6%Only GPT-5.4 Nano measured
GPQA Diamond (Artificial Analysis run)58.1%81.7%GPT-5.4 Nano
Humanity's Last Exam (Artificial Analysis run)7.6%28.3%GPT-5.4 Nano
GPQA Diamond (Epoch AI run)60.5%78.5%GPT-5.4 Nano
ARC-AGINot measured51.5%Only GPT-5.4 Nano measured
ARC-AGI-2Not measured5.7%Only GPT-5.4 Nano measured
Chess puzzlesNot measured45.0%Only GPT-5.4 Nano measured
Mystery game puzzlesNot measured9.0%Only GPT-5.4 Nano measured
LMArena Text: hard prompts13561381GPT-5.4 Nano
LMArena Text: expert13571396GPT-5.4 Nano
LMArena Text: hard prompts in English13691387GPT-5.4 Nano
LMArena Vision: diagramsNot measured1210Only GPT-5.4 Nano measured
LMArena Vision: homeworkNot measured1225Only GPT-5.4 Nano measured
Kagi LLM BenchmarkNot measured39.7%Only GPT-5.4 Nano 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 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
AIMENot measured88.8%Only GPT-5.4 Nano measured
OTIS Mock AIME58.3%87.8%GPT-5.4 Nano
FrontierMath, tiers 1 to 3Not measured44.9%Only GPT-5.4 Nano measured
FrontierMath, tier 4Not measured12.2%Only GPT-5.4 Nano measured
ProofBenchNot measured5.0%Only GPT-5.4 Nano measured
LMArena Text: math13551405GPT-5.4 Nano
LMArena Text: mathematical work13691409GPT-5.4 Nano
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 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
MMLU ProNot measured77.2%Only GPT-5.4 Nano measured
LegalBench (Vals AI)Not measured77.9%Only GPT-5.4 Nano measured
CaseLaw (Vals AI)Not measured51.9%Only GPT-5.4 Nano measured
CorpFin (Vals AI)Not measured61.2%Only GPT-5.4 Nano measured
TaxEval (Vals AI)Not measured67.4%Only GPT-5.4 Nano measured
MortgageTax (Vals AI)Not measured59.1%Only GPT-5.4 Nano measured
MedCode (Vals AI)Not measured41.0%Only GPT-5.4 Nano measured
SimpleQA VerifiedNot measured11.7%Only GPT-5.4 Nano measured
LMArena Text: science13581374GPT-5.4 Nano
LMArena Text: medicine and healthcare13431369GPT-5.4 Nano
LMArena Text: legal and government13571368GPT-5.4 Nano
LMArena Text: business and finance13431366GPT-5.4 Nano
Neither model has a result on the other 6 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 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
Design Arena: websites1194Not measuredOnly GLM 4.7 Flash measured
Design Arena: UI components1205Not measuredOnly GLM 4.7 Flash measured
Design Arena: game dev1134Not measuredOnly GLM 4.7 Flash measured
Design Arena: data viz1123Not measuredOnly GLM 4.7 Flash measured
Design Arena: 3D1120Not measuredOnly GLM 4.7 Flash measured
Design Arena: all code categories1177Not measuredOnly GLM 4.7 Flash measured
Design Arena: SVG1037Not 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 index117
General benchmarks for GLM 4.7 Flash and GPT-5.4 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
SAGE (Vals AI)Not measured38.1%Only GPT-5.4 Nano measured
MedScribe (Vals AI)Not measured77.1%Only GPT-5.4 Nano measured
Vals Multimodal IndexNot measured47.6%Only GPT-5.4 Nano measured
IFBench60.8%75.9%GPT-5.4 Nano
Long context reasoning (AA-LCR)41.7%76.7%GPT-5.4 Nano
DTBenchNot measured80.3%Only GPT-5.4 Nano measured
LMCANot measured36.9%Only GPT-5.4 Nano measured
LMArena Text13511372GPT-5.4 Nano
LMArena Text: instruction following13271362GPT-5.4 Nano
LMArena Text: creative writing12961315GPT-5.4 Nano
LMArena VisionNot measured1196Only GPT-5.4 Nano measured
LMArena Text: English13731381GPT-5.4 Nano
LMArena Text: non-English13301359GPT-5.4 Nano
LMArena Text: Chinese14031391GLM 4.7 Flash
LMArena Text: German13361368GPT-5.4 Nano
LMArena Text: JapaneseNot measured1343Only GPT-5.4 Nano measured
LMArena Text: Korean12831321GPT-5.4 Nano
LMArena Text: French13321395GPT-5.4 Nano
LMArena Text: Spanish13501371GPT-5.4 Nano
LMArena Text: Russian13331363GPT-5.4 Nano
LMArena Text: Polish12911366GPT-5.4 Nano
LMArena Text: multi-turn13421382GPT-5.4 Nano
LMArena Text: longer queries13451365GPT-5.4 Nano
LMArena Text: writing and language13201338GPT-5.4 Nano
LMArena Text: entertainment and media13041325GPT-5.4 Nano
LMArena Vision: EnglishNot measured1202Only GPT-5.4 Nano measured
LMArena Vision: ChineseNot measured1232Only GPT-5.4 Nano measured
LMArena Vision: reading textNot measured1204Only GPT-5.4 Nano measured
LMArena Vision: humorNot measured1161Only GPT-5.4 Nano measured
LMArena Vision: recognizing thingsNot measured1141Only GPT-5.4 Nano measured
LMArena Vision: creative writingNot measured1159Only GPT-5.4 Nano measured
Neither model has a result on the other 15 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 Nano
BenchmarkGLM 4.7 FlashGPT-5.4 NanoLeader
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 Nano$0.0008Fits 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 Nano$0.014Fits 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 Nano$0.052Fits 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 Nano
SpecificationZ.ai GLM 4.7 FlashOpenAI GPT-5.4 Nano
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJanuary 19, 2026March 17, 2026
Context window200K400K
Input $/Mtok$0.0653$0.20
Output $/Mtok$0.40$1.25
Coding indexNot benchmarked44.8
Independent measurements behind it02
Cost per solved taskNot computable$0.14
SourceOpenRouter listingOpenRouter listing

Questions

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

Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 3.1x cheaper ($0.40 vs $1.25 per million) and work measured by τ²-Bench Telecom or LMArena Text: Chinese, where it leads.

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

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; GPT-5.4 Nano costs $0.20 and $1.25. Cost per solved task is known for GPT-5.4 Nano only.

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

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

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

36 benchmarks have a result for both models as of October 22, 2026. GLM 4.7 Flash's coding index rests on 0 independent benchmarks and GPT-5.4 Nano's on 2. Where only one model has a result, the page says so instead of naming a winner.

Compare next