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GLM 5.1 vs Step 3.5 Flash

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 5.1 Replace Step 3.5 Flash
GLM 5.1Z.ai
Coding
49.2
Overall
26.1
Output $/M
$4.40
35
Step 3.5 FlashStepFun
Coding
No data
Overall
17.0
Output $/M
$0.30
0
vs boards won of 35 shared

Decision reading

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; Step 3.5 Flash has none, so the two cannot be ranked on coding.

Step 3.5 Flash has the edge where output tokens cost 14.7x less, and where the context window is larger, 262K against 205K tokens.

Model AGLM 5.1Z.ai49.2/1003 independent benchmarks$0.60 per solved taskModel BStep 3.5 FlashStepFunNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
35
GLM 5.1 only
54
Step 3.5 Flash only
0
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 5.1 49.2 from 3 benchmarks, Step 3.5 Flash not benchmarked.
Widest category
General, 11.2 points apart on average over 19 shared benchmarks.
Widest single gap
LMArena Text: creative writing: GLM 5.1 1453 against Step 3.5 Flash 1357, 15.9 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against Step 3.5 Flash $0.30 per million output tokens, 14.7x apart.
Context window
GLM 5.1 takes 205K 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 5.1BarsStep 3.5 FlashTies
Coding30
Intelligence10
Agentic work10
Reasoning50
Math20
Knowledge40
General190
All shared boards350
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
LMArena WebDev1508Not measuredOnly GLM 5.1 measured
AA Coding Index55.8Not measuredOnly GLM 5.1 measured
LiveCodeBench (Vals AI)81.4%Not measuredOnly GLM 5.1 measured
SWE-bench Verified (Vals AI)76.4%Not measuredOnly GLM 5.1 measured
Vibe Code Bench (Vals AI)31.5%Not measuredOnly GLM 5.1 measured
Code migration (Vals AI)25.8%Not measuredOnly GLM 5.1 measured
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)56.9%Not measuredOnly GLM 5.1 measured
SciCode44.8%Not measuredOnly GLM 5.1 measured
Terminal-Bench Hard (Artificial Analysis run)43.2%32.6%GLM 5.1
WeirdML57.1%Not measuredOnly GLM 5.1 measured
ALE-Bench887.1Not measuredOnly GLM 5.1 measured
LMArena Text: coding14851436GLM 5.1
LMArena Text: software and IT14841434GLM 5.1
LMArena WebDev: React1505Not measuredOnly GLM 5.1 measured
LMArena WebDev: HTML1508Not measuredOnly 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 index10
Intelligence benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
AA Intelligence Index26.117.0GLM 5.1
Epoch Capabilities Index149.8Not measuredOnly GLM 5.1 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
AA Agentic Index23.9Not measuredOnly GLM 5.1 measured
Design Arena: agents building web apps1175Not measuredOnly GLM 5.1 measured
Design Arena: agents building full-stack apps1167Not measuredOnly GLM 5.1 measured
Design Arena: agents building mobile apps1161Not measuredOnly GLM 5.1 measured
Design Arena: agents building Android apps1187Not measuredOnly GLM 5.1 measured
Design Arena: agents building Godot games1053Not measuredOnly GLM 5.1 measured
Design Arena: agents building games1164Not measuredOnly GLM 5.1 measured
Design Arena: HTML slides1170Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1188Not measuredOnly GLM 5.1 measured
Design Arena: spreadsheets1315Not measuredOnly GLM 5.1 measured
Finance Agent (Vals AI)44.8%Not measuredOnly GLM 5.1 measured
Legal Research Bench (Vals AI)27.9%Not measuredOnly GLM 5.1 measured
τ²-Bench Telecom97.7%94.4%GLM 5.1
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
Vending-Bench 2$5,634Not measuredOnly 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 index50
Reasoning benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
GPQA Diamond84.5%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Artificial Analysis run)86.8%83.1%GLM 5.1
Humanity's Last Exam (Artificial Analysis run)30.1%24.5%GLM 5.1
GPQA Diamond (Epoch AI run)89.9%Not measuredOnly GLM 5.1 measured
SimpleBench55.1%Not measuredOnly GLM 5.1 measured
Chess puzzles20.0%Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts14731411GLM 5.1
LMArena Text: expert14781421GLM 5.1
LMArena Text: hard prompts in English14821421GLM 5.1
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
AIME91.9%Not measuredOnly GLM 5.1 measured
OTIS Mock AIME93.3%Not measuredOnly GLM 5.1 measured
FrontierMath, tiers 1 to 336.8%Not measuredOnly GLM 5.1 measured
ProofBench22.2%Not measuredOnly GLM 5.1 measured
LMArena Text: math14731408GLM 5.1
LMArena Text: mathematical work14701421GLM 5.1
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
MMLU Pro86.9%Not measuredOnly GLM 5.1 measured
LegalBench (Vals AI)84.4%Not measuredOnly GLM 5.1 measured
CaseLaw (Vals AI)51.5%Not measuredOnly GLM 5.1 measured
CorpFin (Vals AI)64.5%Not measuredOnly GLM 5.1 measured
TaxEval (Vals AI)71.2%Not measuredOnly GLM 5.1 measured
MedCode (Vals AI)41.6%Not measuredOnly GLM 5.1 measured
SimpleQA Verified34.0%Not measuredOnly GLM 5.1 measured
LMArena Text: science14781415GLM 5.1
LMArena Text: medicine and healthcare14741408GLM 5.1
LMArena Text: legal and government14651408GLM 5.1
LMArena Text: business and finance14521394GLM 5.1
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
Design Arena: websites1290Not measuredOnly GLM 5.1 measured
Design Arena: UI components1292Not measuredOnly GLM 5.1 measured
Design Arena: game dev1265Not measuredOnly GLM 5.1 measured
Design Arena: data viz1366Not measuredOnly GLM 5.1 measured
Design Arena: 3D1336Not measuredOnly GLM 5.1 measured
Design Arena: all code categories1268Not measuredOnly GLM 5.1 measured
Design Arena: SVG1218Not measuredOnly GLM 5.1 measured
Design Arena: ASCII art1142Not measuredOnly 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 index190
General benchmarks for GLM 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 3.5 FlashLeader
Public Benefits Bench (Vals AI)61.8%Not measuredOnly GLM 5.1 measured
MedScribe (Vals AI)72.3%Not measuredOnly GLM 5.1 measured
IFBench76.3%66.5%GLM 5.1
Long context reasoning (AA-LCR)73.7%63.0%GLM 5.1
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text14631403GLM 5.1
LMArena Text: instruction following14531385GLM 5.1
LMArena Text: creative writing14531357GLM 5.1
LMArena Text: English14761417GLM 5.1
LMArena Text: non-English14481385GLM 5.1
LMArena Text: Chinese15151446GLM 5.1
LMArena Text: German14671405GLM 5.1
LMArena Text: Japanese14351353GLM 5.1
LMArena Text: Korean14241351GLM 5.1
LMArena Text: French14701421GLM 5.1
LMArena Text: Spanish14681419GLM 5.1
LMArena Text: Russian14541385GLM 5.1
LMArena Text: Polish14491389GLM 5.1
LMArena Text: multi-turn14731404GLM 5.1
LMArena Text: longer queries14671402GLM 5.1
LMArena Text: writing and language14541372GLM 5.1
LMArena Text: entertainment and media14421360GLM 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 5.1 and Step 3.5 Flash
BenchmarkGLM 5.1Step 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 5.1$0.0036Fits 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 5.1$0.083Fits in one request
Step 3.5 Flash$0.0059Fits in one request

Step 3.5 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 5.1$0.324Exceeds the context window
Step 3.5 Flash$0.023Fits in one request

Step 3.5 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 5.1 and Step 3.5 Flash
SpecificationZ.ai GLM 5.1StepFun Step 3.5 Flash
MakerZ.aiStepFun
WeightsOpen weightsOpen weights
ReleasedApril 7, 2026January 29, 2026
Context window205K262K
Input $/Mtok$1.40$0.10
Output $/Mtok$4.40$0.30
Coding index49.2Not benchmarked
Independent measurements behind it30
Cost per solved task$0.60Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than Step 3.5 Flash for coding?

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; Step 3.5 Flash has none, so the two cannot be ranked on coding. Step 3.5 Flash has the edge where output tokens cost 14.7x less, and where the context window is larger, 262K against 205K tokens.

Which is cheaper, GLM 5.1 or Step 3.5 Flash?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; Step 3.5 Flash costs $0.10 and $0.30. Cost per solved task is known for GLM 5.1 only.

Which has the bigger context window, GLM 5.1 or Step 3.5 Flash?

Step 3.5 Flash, with 262K tokens against 205K.

How many benchmarks is the GLM 5.1 vs Step 3.5 Flash comparison based on?

35 benchmarks have a result for both models as of October 21, 2026. GLM 5.1's coding index rests on 3 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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