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GLM 4.6 vs Llama 4 Scout

GLM 4.6 leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 18.5 to 6.5, and Llama 4 Scout costs 4.4x less per output token ($0.50 vs $2.20 per million). Updated October 22, 2026; 57 benchmarks have a result for both.

Replace GLM 4.6 Replace Llama 4 Scout
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
57
Llama 4 ScoutMeta Llama
Coding
No data
Overall
24.9
Output $/M
$0.50
0
vs boards won of 57 shared

GLM 4.6 or Llama 4 Scout: which to pick

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; Llama 4 Scout has none, so the two cannot be ranked on coding.

Pick Llama 4 Scout for output tokens 4.4x cheaper ($0.50 vs $2.20 per million) and a larger context window (1.31M against 205K tokens).

Model AGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved taskModel BLlama 4 ScoutMeta LlamaNot benchmarkedNo coding benchmark$1.276 per solved task
Shared results
57
GLM 4.6 only
12
Llama 4 Scout only
25
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 4.6 8.8 from 2 benchmarks, Llama 4 Scout not benchmarked.
Widest category
Agentic work, 52.8 points apart on average over 2 shared benchmarks.
Widest single gap
AIME: GLM 4.6 92.7% against Llama 4 Scout 19.0%, 73.8 points apart on a 0 to 100 scale.
Output price
GLM 4.6 $2.20 against Llama 4 Scout $0.50 per million output tokens, 4.4x apart.
Context window
GLM 4.6 takes 205K tokens, Llama 4 Scout 1.31M.

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 4.6BarsLlama 4 ScoutTies
Coding70
Intelligence10
Agentic work20
Reasoning70
Math60
Knowledge100
Web design50
General190
All shared boards570
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
SWE-bench Verified68.2%9.1%GLM 4.6
LMArena WebDev1341Not measuredOnly GLM 4.6 measured
AA Coding Index45.88.2GLM 4.6
LiveCodeBench (Vals AI)81.0%38.5%GLM 4.6
Vibe Code Bench (Vals AI)3.1%Not measuredOnly GLM 4.6 measured
LiveCodeBench (Artificial Analysis run)69.5%29.9%GLM 4.6
SciCodeNot measured21.3%Only Llama 4 Scout measured
Terminal-Bench Hard (Artificial Analysis run)28.8%1.5%GLM 4.6
Terminal-Bench24.5%Not measuredOnly GLM 4.6 measured
ALE-Bench340.8Not measuredOnly GLM 4.6 measured
LMArena Text: coding14491286GLM 4.6
LMArena Text: software and IT14551286GLM 4.6
LMArena WebDev: HTML1350Not measuredOnly GLM 4.6 measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
AA Intelligence Index18.56.5GLM 4.6
Epoch Capabilities IndexNot measured129.6Only Llama 4 Scout measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
AA Agentic IndexNot measured0.5Only Llama 4 Scout measured
Design Arena: agents building full-stack apps1029Not measuredOnly GLM 4.6 measured
Design Arena: agents building mobile apps1096Not measuredOnly GLM 4.6 measured
Design Arena: agents building Android apps1084Not measuredOnly GLM 4.6 measured
Design Arena: agents building Godot games1180Not measuredOnly GLM 4.6 measured
τ²-Bench Telecom76.9%15.5%GLM 4.6
Berkeley Function Calling Leaderboard (BFCL)72.4%28.1%GLM 4.6
BrowseComp-Plus48.2%Not measuredOnly GLM 4.6 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
GPQA Diamond74.5%47.0%GLM 4.6
MMMU Pro (Vals AI)Not measured58.8%Only Llama 4 Scout measured
GPQA Diamond (Artificial Analysis run)78.0%58.7%GLM 4.6
Humanity's Last Exam (Artificial Analysis run)14.5%3.8%GLM 4.6
GPQA Diamond (Epoch AI run)Not measured51.8%Only Llama 4 Scout measured
ARC-AGINot measured0.5%Only Llama 4 Scout measured
ARC-AGI-2Not measured0.0%Only Llama 4 Scout measured
LMArena Text: hard prompts14401266GLM 4.6
LMArena Text: expert14321235GLM 4.6
LMArena Text: hard prompts in English14451293GLM 4.6
LMArena Vision: diagramsNot measured1125Only Llama 4 Scout measured
LMArena Vision: homeworkNot measured1148Only Llama 4 Scout measured
Kagi LLM Benchmark45.7%36.9%GLM 4.6
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
AIME92.7%19.0%GLM 4.6
MATH 500 (Vals AI)Not measured79.2%Only Llama 4 Scout measured
MGSM (Vals AI)89.8%88.0%GLM 4.6
AA Math Index86.014.0GLM 4.6
AIME 2025 (Artificial Analysis run)86.0%14.0%GLM 4.6
OTIS Mock AIMENot measured7.8%Only Llama 4 Scout measured
MATH level 5Not measured62.3%Only Llama 4 Scout measured
LMArena Text: math14321287GLM 4.6
LMArena Text: mathematical work14471286GLM 4.6
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index100
Knowledge benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
MMLU Pro82.2%69.6%GLM 4.6
LegalBench (Vals AI)79.6%72.0%GLM 4.6
CorpFin (Vals AI)56.8%46.8%GLM 4.6
TaxEval (Vals AI)66.2%55.2%GLM 4.6
MortgageTax (Vals AI)Not measured57.8%Only Llama 4 Scout measured
MedQA (Vals AI)92.2%50.9%GLM 4.6
MedCode (Vals AI)Not measured23.3%Only Llama 4 Scout measured
MMLU Pro (Artificial Analysis run)82.9%75.2%GLM 4.6
LMArena Text: science14561278GLM 4.6
LMArena Text: medicine and healthcare14551275GLM 4.6
LMArena Text: legal and government14481285GLM 4.6
LMArena Text: business and finance14161257GLM 4.6
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index50
Web design benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
Design Arena: websites1174750GLM 4.6
Design Arena: UI components1145765GLM 4.6
Design Arena: game dev1150772GLM 4.6
Design Arena: data viz1161896GLM 4.6
Design Arena: 3D1128Not measuredOnly GLM 4.6 measured
Design Arena: all code categories1165789GLM 4.6
Design Arena: SVG1108Not measuredOnly GLM 4.6 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
SAGE (Vals AI)Not measured34.8%Only Llama 4 Scout measured
MedScribe (Vals AI)Not measured50.6%Only Llama 4 Scout measured
IFBench43.4%39.5%GLM 4.6
Long context reasoning (AA-LCR)54.0%27.7%GLM 4.6
DTBenchNot measured57.9%Only Llama 4 Scout measured
LMCANot measured12.0%Only Llama 4 Scout measured
Fiction.LiveBenchNot measured36.0%Only Llama 4 Scout measured
LMArena Text14401279GLM 4.6
LMArena Text: instruction following14101248GLM 4.6
LMArena Text: creative writing14121249GLM 4.6
LMArena VisionNot measured1118Only Llama 4 Scout measured
LMArena Text: English14491304GLM 4.6
LMArena Text: non-English14261252GLM 4.6
LMArena Text: Chinese14991255GLM 4.6
LMArena Text: German14471273GLM 4.6
LMArena Text: Japanese13931206GLM 4.6
LMArena Text: Korean14001207GLM 4.6
LMArena Text: French14591283GLM 4.6
LMArena Text: Spanish14361278GLM 4.6
LMArena Text: Russian14181263GLM 4.6
LMArena Text: Polish14471265GLM 4.6
LMArena Text: multi-turn14271280GLM 4.6
LMArena Text: longer queries14221265GLM 4.6
LMArena Text: writing and language14151269GLM 4.6
LMArena Text: entertainment and media14091242GLM 4.6
LMArena Vision: EnglishNot measured1143Only Llama 4 Scout measured
LMArena Vision: ChineseNot measured1106Only Llama 4 Scout measured
LMArena Vision: reading textNot measured1117Only Llama 4 Scout measured
LMArena Vision: humorNot measured1102Only Llama 4 Scout measured
LMArena Vision: creative writingNot measured1126Only Llama 4 Scout measured
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.6 and Llama 4 Scout
BenchmarkGLM 4.6Llama 4 ScoutLeader
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 4.6$0.0017Fits in one request
Llama 4 Scout$0.0004Fits in one request

Llama 4 Scout costs less

Repository review

50K input + 3K output tokens

GLM 4.6$0.037Fits in one request
Llama 4 Scout$0.010Fits in one request

Llama 4 Scout costs less

Agent loop

200K input + 10K output tokens

GLM 4.6$0.142Exceeds the context window
Llama 4 Scout$0.040Fits in one request

Llama 4 Scout 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 4.6 and Llama 4 Scout
SpecificationZ.ai GLM 4.6Meta Llama 4 Scout
MakerZ.aiMeta Llama
WeightsOpen weightsOpen weights
ReleasedSeptember 30, 2025April 5, 2025
Context window205K1.31M
Input $/Mtok$0.60$0.175
Output $/Mtok$2.20$0.50
Coding index8.8Not benchmarked
Independent measurements behind it20
Cost per solved taskNot computable$1.276
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.6 better than Llama 4 Scout for coding?

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; Llama 4 Scout has none, so the two cannot be ranked on coding. Pick Llama 4 Scout for output tokens 4.4x cheaper ($0.50 vs $2.20 per million) and a larger context window (1.31M against 205K tokens).

Which is cheaper, GLM 4.6 or Llama 4 Scout?

GLM 4.6 costs $0.60 per million input tokens and $2.20 per million output tokens; Llama 4 Scout costs $0.175 and $0.50. Cost per solved task is known for Llama 4 Scout only.

Which has the bigger context window, GLM 4.6 or Llama 4 Scout?

Llama 4 Scout, with 1.31M tokens against 205K.

How many benchmarks is the GLM 4.6 vs Llama 4 Scout comparison based on?

57 benchmarks have a result for both models as of October 22, 2026. GLM 4.6's coding index rests on 2 independent benchmarks and Llama 4 Scout's on 0. Where only one model has a result, the page says so instead of naming a winner.

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