Enter opens the highlighted result. Esc closes.

GLM 4.7 Flash vs GLM 5.1

Updated October 21, 2026. 43 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 GLM 5.1
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
1
GLM 5.1Z.ai
Coding
49.2
Overall
26.1
Output $/M
$4.40
42
vs boards won of 43 shared

Decision reading

Only GLM 5.1 has a coding score, 49.2 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 11.0x 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 BGLM 5.1Z.ai49.2/1003 independent benchmarks$0.60 per solved task
Shared results
43
GLM 4.7 Flash only
0
GLM 5.1 only
46
Like-for-like categories
8 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, GLM 5.1 49.2 from 3 benchmarks.
Widest category
Math, 23.8 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GLM 4.7 Flash 58.3% against GLM 5.1 93.3%, 35.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against GLM 5.1 $4.40 per million output tokens, 11.0x apart.
Context window
GLM 4.7 Flash takes 200K tokens, GLM 5.1 205K.

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 FlashBarsGLM 5.1Ties
Coding03
Intelligence01
Agentic work10
Reasoning06
Math03
Knowledge04
Web design07
General018
All shared boards142
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
LMArena WebDevNot measured1508Only GLM 5.1 measured
AA Coding IndexNot measured55.8Only GLM 5.1 measured
LiveCodeBench (Vals AI)Not measured81.4%Only GLM 5.1 measured
SWE-bench Verified (Vals AI)Not measured76.4%Only GLM 5.1 measured
Vibe Code Bench (Vals AI)Not measured31.5%Only GLM 5.1 measured
Code migration (Vals AI)Not measured25.8%Only GLM 5.1 measured
ProgramBench (Vals AI)Not measured0.0%Only GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)Not measured56.9%Only GLM 5.1 measured
SciCodeNot measured44.8%Only GLM 5.1 measured
Terminal-Bench Hard (Artificial Analysis run)22.0%43.2%GLM 5.1
WeirdMLNot measured57.1%Only GLM 5.1 measured
ALE-BenchNot measured887.1Only GLM 5.1 measured
LMArena Text: coding13821485GLM 5.1
LMArena Text: software and IT13891484GLM 5.1
LMArena WebDev: ReactNot measured1505Only GLM 5.1 measured
LMArena WebDev: HTMLNot measured1508Only GLM 5.1 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
AA Intelligence Index14.926.1GLM 5.1
Epoch Capabilities IndexNot measured149.8Only GLM 5.1 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
AA Agentic IndexNot measured23.9Only GLM 5.1 measured
Design Arena: agents building web appsNot measured1175Only GLM 5.1 measured
Design Arena: agents building full-stack appsNot measured1167Only GLM 5.1 measured
Design Arena: agents building mobile appsNot measured1161Only GLM 5.1 measured
Design Arena: agents building Android appsNot measured1187Only GLM 5.1 measured
Design Arena: agents building Godot gamesNot measured1053Only GLM 5.1 measured
Design Arena: agents building gamesNot measured1164Only GLM 5.1 measured
Design Arena: HTML slidesNot measured1170Only GLM 5.1 measured
Design Arena: PowerPoint slidesNot measured1188Only GLM 5.1 measured
Design Arena: spreadsheetsNot measured1315Only GLM 5.1 measured
Finance Agent (Vals AI)Not measured44.8%Only GLM 5.1 measured
Legal Research Bench (Vals AI)Not measured27.9%Only GLM 5.1 measured
τ²-Bench Telecom98.8%97.7%GLM 4.7 Flash
APEX-AgentsNot measured40.9%Only GLM 5.1 measured
Vending-Bench 2Not measured$5,634Only GLM 5.1 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
GPQA DiamondNot measured84.5%Only GLM 5.1 measured
GPQA Diamond (Artificial Analysis run)58.1%86.8%GLM 5.1
Humanity's Last Exam (Artificial Analysis run)7.6%30.1%GLM 5.1
GPQA Diamond (Epoch AI run)60.5%89.9%GLM 5.1
SimpleBenchNot measured55.1%Only GLM 5.1 measured
Chess puzzlesNot measured20.0%Only GLM 5.1 measured
LMArena Text: hard prompts13561473GLM 5.1
LMArena Text: expert13571478GLM 5.1
LMArena Text: hard prompts in English13691482GLM 5.1
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
AIMENot measured91.9%Only GLM 5.1 measured
OTIS Mock AIME58.3%93.3%GLM 5.1
FrontierMath, tiers 1 to 3Not measured36.8%Only GLM 5.1 measured
ProofBenchNot measured22.2%Only GLM 5.1 measured
LMArena Text: math13551473GLM 5.1
LMArena Text: mathematical work13691470GLM 5.1
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
MMLU ProNot measured86.9%Only GLM 5.1 measured
LegalBench (Vals AI)Not measured84.4%Only GLM 5.1 measured
CaseLaw (Vals AI)Not measured51.5%Only GLM 5.1 measured
CorpFin (Vals AI)Not measured64.5%Only GLM 5.1 measured
TaxEval (Vals AI)Not measured71.2%Only GLM 5.1 measured
MedCode (Vals AI)Not measured41.6%Only GLM 5.1 measured
SimpleQA VerifiedNot measured34.0%Only GLM 5.1 measured
LMArena Text: science13581478GLM 5.1
LMArena Text: medicine and healthcare13431474GLM 5.1
LMArena Text: legal and government13571465GLM 5.1
LMArena Text: business and finance13431452GLM 5.1
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
Design Arena: websites11941290GLM 5.1
Design Arena: UI components12081292GLM 5.1
Design Arena: game dev11351265GLM 5.1
Design Arena: data viz11231366GLM 5.1
Design Arena: 3D11211336GLM 5.1
Design Arena: all code categories11781268GLM 5.1
Design Arena: SVG10381218GLM 5.1
Design Arena: ASCII artNot measured1142Only GLM 5.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for GLM 4.7 Flash and GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
Public Benefits Bench (Vals AI)Not measured61.8%Only GLM 5.1 measured
MedScribe (Vals AI)Not measured72.3%Only GLM 5.1 measured
IFBench60.8%76.3%GLM 5.1
Long context reasoning (AA-LCR)41.7%73.7%GLM 5.1
ExploitBenchNot measured18.1%Only GLM 5.1 measured
LMArena Text13511463GLM 5.1
LMArena Text: instruction following13271453GLM 5.1
LMArena Text: creative writing12961453GLM 5.1
LMArena Text: English13731476GLM 5.1
LMArena Text: non-English13301448GLM 5.1
LMArena Text: Chinese14031515GLM 5.1
LMArena Text: German13361467GLM 5.1
LMArena Text: JapaneseNot measured1435Only GLM 5.1 measured
LMArena Text: Korean12831424GLM 5.1
LMArena Text: French13321470GLM 5.1
LMArena Text: Spanish13501468GLM 5.1
LMArena Text: Russian13331454GLM 5.1
LMArena Text: Polish12911449GLM 5.1
LMArena Text: multi-turn13421473GLM 5.1
LMArena Text: longer queries13451467GLM 5.1
LMArena Text: writing and language13201454GLM 5.1
LMArena Text: entertainment and media13041442GLM 5.1
Neither model has a result on the other 24 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 GLM 5.1
BenchmarkGLM 4.7 FlashGLM 5.1Leader
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
GLM 5.1$0.0036Fits 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
GLM 5.1$0.083Fits 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
GLM 5.1$0.324Exceeds 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 GLM 5.1
SpecificationZ.ai GLM 4.7 FlashZ.ai GLM 5.1
MakerZ.aiZ.ai
WeightsOpen weightsOpen weights
ReleasedJanuary 19, 2026April 7, 2026
Context window200K205K
Input $/Mtok$0.0653$1.40
Output $/Mtok$0.40$4.40
Coding indexNot benchmarked49.2
Independent measurements behind it03
Cost per solved taskNot computable$0.60
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than GLM 5.1 for coding?

Only GLM 5.1 has a coding score, 49.2 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 11.0x less, and where the benchmark that matters is τ²-Bench Telecom, where it leads.

Which is cheaper, GLM 4.7 Flash or GLM 5.1?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; GLM 5.1 costs $1.40 and $4.40. Cost per solved task is known for GLM 5.1 only.

Which has the bigger context window, GLM 4.7 Flash or GLM 5.1?

GLM 5.1, with 205K tokens against 200K.

How many benchmarks is the GLM 4.7 Flash vs GLM 5.1 comparison based on?

43 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 GLM 5.1's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next