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GLM 4.5 vs GLM 4.7 Flash

GLM 4.7 Flash leads GLM 4.5 on the Artificial Analysis Intelligence Index, 14.9 to 12.8, and GLM 4.7 Flash costs 5.5x less per output token ($0.40 vs $2.20 per million). Updated October 21, 2026; 41 benchmarks have a result for both.

Replace GLM 4.5 Replace GLM 4.7 Flash
GLM 4.5Z.ai
Coding
No data
Overall
No data
Output $/M
$2.20
34
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
6
vs boards won of 41 shared, 1 tied

GLM 4.5 or GLM 4.7 Flash: which to pick

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

Pick GLM 4.5 for work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.

Model AGLM 4.5Z.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
41
GLM 4.5 only
20
GLM 4.7 Flash only
2
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 4.5 not benchmarked, GLM 4.7 Flash not benchmarked.
Widest category
Agentic work, 55.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 43.0% against GLM 4.7 Flash 98.8%, 55.8 points apart on a 0 to 100 scale.
Output price
GLM 4.5 $2.20 against GLM 4.7 Flash $0.40 per million output tokens, 5.5x apart.
Context window
GLM 4.5 takes 131K tokens, GLM 4.7 Flash 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 4.5BarsGLM 4.7 FlashTies
Coding201 tie
Intelligence01
Agentic work01
Reasoning50
Math20
Knowledge40
Web design43
General171
All shared boards3461 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
SWE-bench Verified64.2%Not measuredOnly GLM 4.5 measured
LiveCodeBench (Vals AI)67.5%Not measuredOnly GLM 4.5 measured
LiveCodeBench (Artificial Analysis run)73.8%Not measuredOnly GLM 4.5 measured
Terminal-Bench Hard (Artificial Analysis run)22.0%22.0%Tie
WeirdML40.6%Not measuredOnly GLM 4.5 measured
ALE-Bench344.8Not measuredOnly GLM 4.5 measured
LMArena Text: coding14341382GLM 4.5
LMArena Text: software and IT14401389GLM 4.5
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
AA Intelligence Index12.814.9GLM 4.7 Flash
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
τ²-Bench Telecom43.0%98.8%GLM 4.7 Flash
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
GPQA Diamond72.2%Not measuredOnly GLM 4.5 measured
GPQA Diamond (Artificial Analysis run)78.2%58.1%GLM 4.5
Humanity's Last Exam (Artificial Analysis run)13.0%7.6%GLM 4.5
GPQA Diamond (Epoch AI run)Not measured60.5%Only GLM 4.7 Flash measured
LMArena Text: hard prompts14291356GLM 4.5
LMArena Text: expert14331357GLM 4.5
LMArena Text: hard prompts in English14291369GLM 4.5
Kagi LLM Benchmark57.9%Not measuredOnly GLM 4.5 measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
AIME86.7%Not measuredOnly GLM 4.5 measured
MATH 500 (Vals AI)94.0%Not measuredOnly GLM 4.5 measured
MGSM (Vals AI)90.8%Not measuredOnly GLM 4.5 measured
AA Math Index73.7Not measuredOnly GLM 4.5 measured
AIME 2025 (Artificial Analysis run)73.7%Not measuredOnly GLM 4.5 measured
OTIS Mock AIMENot measured58.3%Only GLM 4.7 Flash measured
LMArena Text: math14271355GLM 4.5
LMArena Text: mathematical work14301369GLM 4.5
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
MMLU Pro81.2%Not measuredOnly GLM 4.5 measured
LegalBench (Vals AI)75.6%Not measuredOnly GLM 4.5 measured
CorpFin (Vals AI)61.0%Not measuredOnly GLM 4.5 measured
TaxEval (Vals AI)72.4%Not measuredOnly GLM 4.5 measured
MedQA (Vals AI)90.0%Not measuredOnly GLM 4.5 measured
MMLU Pro (Artificial Analysis run)83.5%Not measuredOnly GLM 4.5 measured
LMArena Text: science14441358GLM 4.5
LMArena Text: medicine and healthcare14551343GLM 4.5
LMArena Text: legal and government14381357GLM 4.5
LMArena Text: business and finance14201343GLM 4.5
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index43
Web design benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
Design Arena: websites11701194GLM 4.7 Flash
Design Arena: UI components11441208GLM 4.7 Flash
Design Arena: game dev11451135GLM 4.5
Design Arena: data viz11591123GLM 4.5
Design Arena: 3D11701121GLM 4.5
Design Arena: all code categories11651178GLM 4.7 Flash
Design Arena: SVG10961038GLM 4.5
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index171
General benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
IFBench44.1%60.8%GLM 4.7 Flash
Long context reasoning (AA-LCR)52.7%41.7%GLM 4.5
Creative writing (Lech Mazur)73.4%Not measuredOnly GLM 4.5 measured
LMArena Text14301351GLM 4.5
LMArena Text: instruction following14041327GLM 4.5
LMArena Text: creative writing13951296GLM 4.5
LMArena Text: English14371373GLM 4.5
LMArena Text: non-English14171330GLM 4.5
LMArena Text: Chinese14651403GLM 4.5
LMArena Text: German14071336GLM 4.5
LMArena Text: Japanese1415Not measuredOnly GLM 4.5 measured
LMArena Text: Korean13801283GLM 4.5
LMArena Text: French14181332GLM 4.5
LMArena Text: Spanish14541350GLM 4.5
LMArena Text: Russian14131333GLM 4.5
LMArena Text: Polish14221291GLM 4.5
LMArena Text: multi-turn14151342GLM 4.5
LMArena Text: longer queries14121345GLM 4.5
LMArena Text: writing and language14031320GLM 4.5
LMArena Text: entertainment and media14041304GLM 4.5
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.5 and GLM 4.7 Flash
BenchmarkGLM 4.5GLM 4.7 FlashLeader
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 4.5$0.0017Fits in one request
GLM 4.7 Flash$0.0003Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

GLM 4.5$0.037Fits in one request
GLM 4.7 Flash$0.0045Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 4.5$0.142Exceeds the context window
GLM 4.7 Flash$0.017Exceeds 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 4.5 and GLM 4.7 Flash
SpecificationZ.ai GLM 4.5Z.ai GLM 4.7 Flash
MakerZ.aiZ.ai
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025January 19, 2026
Context window131K200K
Input $/Mtok$0.60$0.0653
Output $/Mtok$2.20$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 better than GLM 4.7 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5 for work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.

Which is cheaper, GLM 4.5 or GLM 4.7 Flash?

GLM 4.5 costs $0.60 per million input tokens and $2.20 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.5 or GLM 4.7 Flash?

GLM 4.7 Flash, with 200K tokens against 131K.

How many benchmarks is the GLM 4.5 vs GLM 4.7 Flash comparison based on?

41 benchmarks have a result for both models as of October 21, 2026. GLM 4.5's coding index rests on 0 independent benchmarks and GLM 4.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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