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GLM 5.1 vs Qwen3.5-35B-A3B

GLM 5.1 leads Qwen3.5-35B-A3B on the Artificial Analysis Intelligence Index, 26.1 to 19.3, and Qwen3.5-35B-A3B costs 3.4x less per output token ($1.30 vs $4.40 per million). Updated October 22, 2026; 44 benchmarks have a result for both.

Replace GLM 5.1 Replace Qwen3.5-35B-A3B
GLM 5.1Z.ai
Coding
49.2
Overall
57.5
Output $/M
$4.40
44
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
0
vs boards won of 44 shared

GLM 5.1 or Qwen3.5-35B-A3B: which to pick

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-35B-A3B for output tokens 3.4x cheaper ($1.30 vs $4.40 per million) and a larger context window (262K against 205K tokens).

Model AGLM 5.1Z.ai49.2/1003 independent benchmarks$0.60 per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
44
GLM 5.1 only
47
Qwen3.5-35B-A3B only
2
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 5.1 49.2 from 3 benchmarks, Qwen3.5-35B-A3B not benchmarked.
Widest category
Coding, 25.4 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: GLM 5.1 1505 against Qwen3.5-35B-A3B 1238, 44.5 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against Qwen3.5-35B-A3B $1.30 per million output tokens, 3.4x apart.
Context window
GLM 5.1 takes 205K tokens, Qwen3.5-35B-A3B 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 5.1BarsQwen3.5-35B-A3BTies
Coding70
Intelligence20
Agentic work20
Reasoning60
Math40
Knowledge40
General190
All shared boards440
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for GLM 5.1 and Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
LMArena WebDev15081254GLM 5.1
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%26.5%GLM 5.1
WeirdML57.1%Not measuredOnly GLM 5.1 measured
ALE-Bench887.1221.8GLM 5.1
LMArena Text: coding14851410GLM 5.1
LMArena Text: software and IT14841415GLM 5.1
LMArena WebDev: React15051238GLM 5.1
LMArena WebDev: HTML15081301GLM 5.1
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GLM 5.1 and Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
AA Intelligence Index26.119.3GLM 5.1
Epoch Capabilities Index149.8142.5GLM 5.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for GLM 5.1 and Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
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 apps1160Not measuredOnly GLM 5.1 measured
Design Arena: agents building Android apps1181Not 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 slides1109Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1162Not 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%89.2%GLM 5.1
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
Vending-Bench 2$5,634$463GLM 5.1
MCP Atlas75.6%Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for GLM 5.1 and Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
GPQA Diamond84.5%Not measuredOnly GLM 5.1 measured
GPQA Diamond (Artificial Analysis run)86.8%84.5%GLM 5.1
Humanity's Last Exam (Artificial Analysis run)30.1%21.0%GLM 5.1
GPQA Diamond (Epoch AI run)89.9%83.5%GLM 5.1
SimpleBench55.1%Not measuredOnly GLM 5.1 measured
Chess puzzles20.0%Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts14731400GLM 5.1
LMArena Text: expert14781408GLM 5.1
LMArena Text: hard prompts in English14821411GLM 5.1
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for GLM 5.1 and Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
AIME91.9%Not measuredOnly GLM 5.1 measured
OTIS Mock AIME93.3%70.0%GLM 5.1
FrontierMath, tiers 1 to 336.8%Not measuredOnly GLM 5.1 measured
ProofBench22.2%Not measuredOnly GLM 5.1 measured
LMArena Text: math14731404GLM 5.1
LMArena Text: mathematical work14701410GLM 5.1
MathArena20.1%14.7%GLM 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 Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
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: science14781413GLM 5.1
LMArena Text: medicine and healthcare14741421GLM 5.1
LMArena Text: legal and government14651399GLM 5.1
LMArena Text: business and finance14521394GLM 5.1
Neither model has a result on the other 9 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 Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
Design Arena: websites1290Not measuredOnly GLM 5.1 measured
Design Arena: UI components1292Not measuredOnly GLM 5.1 measured
Design Arena: game dev1264Not 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: SVG1217Not measuredOnly GLM 5.1 measured
Design Arena: ASCII art1141Not 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 Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
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%72.5%GLM 5.1
Long context reasoning (AA-LCR)73.7%72.0%GLM 5.1
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text14631395GLM 5.1
LMArena Text: instruction following14531379GLM 5.1
LMArena Text: creative writing14531347GLM 5.1
LMArena Text: English14761407GLM 5.1
LMArena Text: non-English14481378GLM 5.1
LMArena Text: Chinese15151457GLM 5.1
LMArena Text: German14671367GLM 5.1
LMArena Text: Japanese14351326GLM 5.1
LMArena Text: Korean14241355GLM 5.1
LMArena Text: French14701412GLM 5.1
LMArena Text: Spanish14681390GLM 5.1
LMArena Text: Russian14541376GLM 5.1
LMArena Text: Polish14491385GLM 5.1
LMArena Text: multi-turn14731390GLM 5.1
LMArena Text: longer queries14671389GLM 5.1
LMArena Text: writing and language14541365GLM 5.1
LMArena Text: entertainment and media14421347GLM 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 Qwen3.5-35B-A3B
BenchmarkGLM 5.1Qwen3.5-35B-A3BLeader
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
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

GLM 5.1$0.083Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

GLM 5.1$0.324Exceeds the context window
Qwen3.5-35B-A3B$0.045Fits in one request

Qwen3.5-35B-A3B 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 Qwen3.5-35B-A3B
SpecificationZ.ai GLM 5.1Qwen3.5-35B-A3B
MakerZ.aiQwen
WeightsOpen weightsOpen weights
ReleasedApril 7, 2026February 25, 2026
Context window205K262K
Input $/Mtok$1.40$0.1625
Output $/Mtok$4.40$1.30
Coding index49.2Not benchmarked
Independent measurements behind it31
Cost per solved task$0.60Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than Qwen3.5-35B-A3B for coding?

Only GLM 5.1 has a coding score, 49.2 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding. Pick Qwen3.5-35B-A3B for output tokens 3.4x cheaper ($1.30 vs $4.40 per million) and a larger context window (262K against 205K tokens).

Which is cheaper, GLM 5.1 or Qwen3.5-35B-A3B?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for GLM 5.1 only.

Which has the bigger context window, GLM 5.1 or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B, with 262K tokens against 205K.

How many benchmarks is the GLM 5.1 vs Qwen3.5-35B-A3B comparison based on?

44 benchmarks have a result for both models as of October 22, 2026. GLM 5.1's coding index rests on 3 independent benchmarks and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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