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GLM 4.7 Flash vs Step 3.5 Flash

Step 3.5 Flash leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 17.0 to 14.9, and Step 3.5 Flash costs 1.3x less per output token ($0.30 vs $0.40 per million). Updated October 22, 2026; 34 benchmarks have a result for both.

Replace GLM 4.7 Flash Replace Step 3.5 Flash
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
1
Step 3.5 FlashStepFun
Coding
No data
Overall
No data
Output $/M
$0.30
33
vs boards won of 34 shared

GLM 4.7 Flash or Step 3.5 Flash: which to pick

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

Pick GLM 4.7 Flash for work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BStep 3.5 FlashStepFunNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
34
GLM 4.7 Flash only
9
Step 3.5 Flash only
1
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, Step 3.5 Flash not benchmarked.
Widest category
Reasoning, 14.1 points apart on average over 5 shared benchmarks.
Widest single gap
GPQA Diamond (Artificial Analysis run): GLM 4.7 Flash 58.1% against Step 3.5 Flash 83.1%, 25.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against Step 3.5 Flash $0.30 per million output tokens, 1.3x apart.
Context window
GLM 4.7 Flash takes 200K tokens, Step 3.5 Flash 262K.

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 FlashBarsStep 3.5 FlashTies
Coding03
Intelligence01
Agentic work10
Reasoning05
Math02
Knowledge04
General018
All shared boards133
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.7 Flash and Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
Terminal-Bench Hard (Artificial Analysis run)22.0%32.6%Step 3.5 Flash
LMArena Text: coding13821436Step 3.5 Flash
LMArena Text: software and IT13891434Step 3.5 Flash
Neither model has a result on the other 36 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.7 Flash and Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
AA Intelligence Index14.917.0Step 3.5 Flash
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
τ²-Bench Telecom98.8%94.4%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 index05
Reasoning benchmarks for GLM 4.7 Flash and Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
GPQA Diamond (Artificial Analysis run)58.1%83.1%Step 3.5 Flash
Humanity's Last Exam (Artificial Analysis run)7.6%24.5%Step 3.5 Flash
GPQA Diamond (Epoch AI run)60.5%Not measuredOnly GLM 4.7 Flash measured
LMArena Text: hard prompts13561411Step 3.5 Flash
LMArena Text: expert13571421Step 3.5 Flash
LMArena Text: hard prompts in English13691421Step 3.5 Flash
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 4.7 Flash and Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
OTIS Mock AIME58.3%Not measuredOnly GLM 4.7 Flash measured
LMArena Text: math13551408Step 3.5 Flash
LMArena Text: mathematical work13691421Step 3.5 Flash
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.7 Flash and Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
LMArena Text: science13581415Step 3.5 Flash
LMArena Text: medicine and healthcare13431408Step 3.5 Flash
LMArena Text: legal and government13571408Step 3.5 Flash
LMArena Text: business and finance13431394Step 3.5 Flash
Neither model has a result on the other 14 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 Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
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 index018
General benchmarks for GLM 4.7 Flash and Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 FlashLeader
IFBench60.8%66.5%Step 3.5 Flash
Long context reasoning (AA-LCR)41.7%63.0%Step 3.5 Flash
LMArena Text13511403Step 3.5 Flash
LMArena Text: instruction following13271385Step 3.5 Flash
LMArena Text: creative writing12961357Step 3.5 Flash
LMArena Text: English13731417Step 3.5 Flash
LMArena Text: non-English13301385Step 3.5 Flash
LMArena Text: Chinese14031446Step 3.5 Flash
LMArena Text: German13361405Step 3.5 Flash
LMArena Text: JapaneseNot measured1353Only Step 3.5 Flash measured
LMArena Text: Korean12831351Step 3.5 Flash
LMArena Text: French13321421Step 3.5 Flash
LMArena Text: Spanish13501419Step 3.5 Flash
LMArena Text: Russian13331385Step 3.5 Flash
LMArena Text: Polish12911389Step 3.5 Flash
LMArena Text: multi-turn13421404Step 3.5 Flash
LMArena Text: longer queries13451402Step 3.5 Flash
LMArena Text: writing and language13201372Step 3.5 Flash
LMArena Text: entertainment and media13041360Step 3.5 Flash
Neither model has a result on the other 27 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 Step 3.5 Flash
BenchmarkGLM 4.7 FlashStep 3.5 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 4.7 Flash$0.0003Fits in one request
Step 3.5 Flash$0.0003Fits in one request

Step 3.5 Flash costs less

Repository review

50K input + 3K output tokens

GLM 4.7 Flash$0.0045Fits in one request
Step 3.5 Flash$0.0059Fits 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
Step 3.5 Flash$0.023Fits 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 Step 3.5 Flash
SpecificationZ.ai GLM 4.7 FlashStepFun Step 3.5 Flash
MakerZ.aiStepFun
WeightsOpen weightsOpen weights
ReleasedJanuary 19, 2026January 29, 2026
Context window200K262K
Input $/Mtok$0.0653$0.10
Output $/Mtok$0.40$0.30
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 Step 3.5 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, GLM 4.7 Flash or Step 3.5 Flash?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; Step 3.5 Flash costs $0.10 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.7 Flash or Step 3.5 Flash?

Step 3.5 Flash, with 262K tokens against 200K.

How many benchmarks is the GLM 4.7 Flash vs Step 3.5 Flash comparison based on?

34 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 Step 3.5 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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