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GLM 4.7 Flash vs o1

Updated October 21, 2026. 35 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 o1
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
9
o1OpenAI
Coding
No data
Overall
15.2
Output $/M
$60.00
26
vs boards won of 35 shared

Decision reading

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

GLM 4.7 Flash has the edge where output tokens cost 150.0x less, and where what matters is 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 Bo1OpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
35
GLM 4.7 Flash only
8
o1 only
33
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, o1 not benchmarked.
Widest category
Agentic work, 36.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.7 Flash 98.8% against o1 62.6%, 36.3 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against o1 $60.00 per million output tokens, 150.0x 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 FlashBarso1Ties
Coding30
Intelligence01
Agentic work10
Reasoning15
Math03
Knowledge13
General314
All shared boards926
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 4.7 Flash and o1
BenchmarkGLM 4.7 Flasho1Leader
Aider polyglotNot measured61.7%Only o1 measured
AA Coding IndexNot measured39.7Only o1 measured
LiveCodeBench (Vals AI)Not measured50.3%Only o1 measured
LiveCodeBench (Artificial Analysis run)Not measured67.9%Only o1 measured
Terminal-Bench Hard (Artificial Analysis run)22.0%12.9%GLM 4.7 Flash
WeirdMLNot measured46.1%Only o1 measured
LMArena Text: coding13821367GLM 4.7 Flash
LMArena Text: software and IT13891366GLM 4.7 Flash
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.7 Flash and o1
BenchmarkGLM 4.7 Flasho1Leader
AA Intelligence Index14.915.2o1
Epoch Capabilities IndexNot measured141.7Only o1 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and o1
BenchmarkGLM 4.7 Flasho1Leader
τ²-Bench Telecom98.8%62.6%GLM 4.7 Flash
METR time horizonsNot measured51.1%Only o1 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
Reasoning benchmarks for GLM 4.7 Flash and o1
BenchmarkGLM 4.7 Flasho1Leader
GPQA DiamondNot measured73.2%Only o1 measured
MMMU Pro (Vals AI)Not measured77.4%Only o1 measured
GPQA Diamond (Artificial Analysis run)58.1%74.7%o1
Humanity's Last Exam (Artificial Analysis run)7.6%7.0%GLM 4.7 Flash
GPQA Diamond (Epoch AI run)60.5%76.8%o1
ARC-AGINot measured30.7%Only o1 measured
SimpleBenchNot measured40.1%Only o1 measured
Chess puzzlesNot measured10.0%Only o1 measured
VPCTNot measured37.0%Only o1 measured
LMArena Text: hard prompts13561371o1
LMArena Text: expert13571361o1
LMArena Text: hard prompts in English13691372o1
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GLM 4.7 Flash and o1
BenchmarkGLM 4.7 Flasho1Leader
AIMENot measured71.5%Only o1 measured
MATH 500 (Vals AI)Not measured90.4%Only o1 measured
MGSM (Vals AI)Not measured89.3%Only o1 measured
OTIS Mock AIME58.3%73.3%o1
FrontierMath, tiers 1 to 3Not measured14.7%Only o1 measured
MATH level 5Not measured94.7%Only o1 measured
LMArena Text: math13551388o1
LMArena Text: mathematical work13691390o1
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
Knowledge benchmarks for GLM 4.7 Flash and o1
BenchmarkGLM 4.7 Flasho1Leader
MMLU ProNot measured83.5%Only o1 measured
LegalBench (Vals AI)Not measured80.4%Only o1 measured
TaxEval (Vals AI)Not measured74.3%Only o1 measured
MedQA (Vals AI)Not measured96.5%Only o1 measured
MMLU Pro (Artificial Analysis run)Not measured84.1%Only o1 measured
SimpleQA VerifiedNot measured41.1%Only o1 measured
GeoBenchNot measured80.0%Only o1 measured
LMArena Text: science13581369o1
LMArena Text: medicine and healthcare13431355o1
LMArena Text: legal and government13571368o1
LMArena Text: business and finance13431328GLM 4.7 Flash
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 o1
BenchmarkGLM 4.7 Flasho1Leader
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 index314
General benchmarks for GLM 4.7 Flash and o1
BenchmarkGLM 4.7 Flasho1Leader
IFBench60.8%70.3%o1
Long context reasoning (AA-LCR)41.7%65.0%o1
DTBenchNot measured74.7%Only o1 measured
LMCANot measured22.3%Only o1 measured
Fiction.LiveBenchNot measured83.3%Only o1 measured
Creative writing (Lech Mazur)Not measured70.2%Only o1 measured
LMArena Text13511366o1
LMArena Text: instruction following13271367o1
LMArena Text: creative writing12961347o1
LMArena VisionNot measured1168Only o1 measured
LMArena Text: English13731372GLM 4.7 Flash
LMArena Text: non-English13301358o1
LMArena Text: Chinese14031394GLM 4.7 Flash
LMArena Text: German13361337o1
LMArena Text: JapaneseNot measured1346Only o1 measured
LMArena Text: Korean12831396o1
LMArena Text: French13321344o1
LMArena Text: Spanish13501345GLM 4.7 Flash
LMArena Text: Russian13331356o1
LMArena Text: Polish1291Not measuredOnly GLM 4.7 Flash measured
LMArena Text: multi-turn13421355o1
LMArena Text: longer queries13451378o1
LMArena Text: writing and language13201360o1
LMArena Text: entertainment and media13041358o1
LMArena Vision: EnglishNot measured1162Only o1 measured
LMArena Vision: ChineseNot measured1235Only o1 measured
Neither model has a result on the other 20 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 o1
BenchmarkGLM 4.7 Flasho1Leader
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
o1$0.045Fits 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
o1$0.930Fits 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
o1$3.60Exceeds 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 o1
SpecificationZ.ai GLM 4.7 FlashOpenAI o1
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJanuary 19, 2026December 17, 2024
Context window200K200K
Input $/Mtok$0.0653$15.00
Output $/Mtok$0.40$60.00
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 o1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. GLM 4.7 Flash has the edge where output tokens cost 150.0x less, and where what matters is AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, GLM 4.7 Flash or o1?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; o1 costs $15.00 and $60.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.7 Flash or o1?

Neither: both take 200K tokens.

How many benchmarks is the GLM 4.7 Flash vs o1 comparison based on?

35 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 o1's on 0. Where only one model has a result, the page says so instead of naming a winner.

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