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GLM 4.7 Flash vs Llama 4 Scout

GLM 4.7 Flash leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 14.9 to 6.5, and GLM 4.7 Flash costs 1.3x less per output token ($0.40 vs $0.50 per million). Updated October 22, 2026; 41 benchmarks have a result for both.

Replace GLM 4.7 Flash Replace Llama 4 Scout
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
40
Llama 4 ScoutMeta Llama
Coding
No data
Overall
24.9
Output $/M
$0.50
1
vs boards won of 41 shared

GLM 4.7 Flash or Llama 4 Scout: which to pick

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

Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and work measured by GPQA Diamond (Artificial Analysis run), where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BLlama 4 ScoutMeta LlamaNot benchmarkedNo coding benchmark$1.276 per solved task
Shared results
41
GLM 4.7 Flash only
2
Llama 4 Scout only
41
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 4.7 Flash not benchmarked, Llama 4 Scout not benchmarked.
Widest category
Agentic work, 83.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.7 Flash 98.8% against Llama 4 Scout 15.5%, 83.3 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against Llama 4 Scout $0.50 per million output tokens, 1.3x apart.
Context window
GLM 4.7 Flash takes 200K 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 4.7 FlashBarsLlama 4 ScoutTies
Coding30
Intelligence10
Agentic work10
Reasoning51
Math30
Knowledge40
Web design50
General180
All shared boards401
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
SWE-bench VerifiedNot measured9.1%Only Llama 4 Scout measured
AA Coding IndexNot measured8.2Only Llama 4 Scout measured
LiveCodeBench (Vals AI)Not measured38.5%Only Llama 4 Scout measured
LiveCodeBench (Artificial Analysis run)Not measured29.9%Only Llama 4 Scout measured
SciCodeNot measured21.3%Only Llama 4 Scout measured
Terminal-Bench Hard (Artificial Analysis run)22.0%1.5%GLM 4.7 Flash
LMArena Text: coding13821286GLM 4.7 Flash
LMArena Text: software and IT13891286GLM 4.7 Flash
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
AA Intelligence Index14.96.5GLM 4.7 Flash
Epoch Capabilities IndexNot measured129.6Only Llama 4 Scout measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
AA Agentic IndexNot measured0.5Only Llama 4 Scout measured
τ²-Bench Telecom98.8%15.5%GLM 4.7 Flash
Berkeley Function Calling Leaderboard (BFCL)Not measured28.1%Only Llama 4 Scout measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
Reasoning benchmarks for GLM 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
GPQA DiamondNot measured47.0%Only Llama 4 Scout measured
MMMU Pro (Vals AI)Not measured58.8%Only Llama 4 Scout measured
GPQA Diamond (Artificial Analysis run)58.1%58.7%Llama 4 Scout
Humanity's Last Exam (Artificial Analysis run)7.6%3.8%GLM 4.7 Flash
GPQA Diamond (Epoch AI run)60.5%51.8%GLM 4.7 Flash
ARC-AGINot measured0.5%Only Llama 4 Scout measured
ARC-AGI-2Not measured0.0%Only Llama 4 Scout measured
LMArena Text: hard prompts13561266GLM 4.7 Flash
LMArena Text: expert13571235GLM 4.7 Flash
LMArena Text: hard prompts in English13691293GLM 4.7 Flash
LMArena Vision: diagramsNot measured1125Only Llama 4 Scout measured
LMArena Vision: homeworkNot measured1148Only Llama 4 Scout measured
Kagi LLM BenchmarkNot measured36.9%Only Llama 4 Scout measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for GLM 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
AIMENot measured19.0%Only Llama 4 Scout measured
MATH 500 (Vals AI)Not measured79.2%Only Llama 4 Scout measured
MGSM (Vals AI)Not measured88.0%Only Llama 4 Scout measured
AA Math IndexNot measured14.0Only Llama 4 Scout measured
AIME 2025 (Artificial Analysis run)Not measured14.0%Only Llama 4 Scout measured
OTIS Mock AIME58.3%7.8%GLM 4.7 Flash
MATH level 5Not measured62.3%Only Llama 4 Scout measured
LMArena Text: math13551287GLM 4.7 Flash
LMArena Text: mathematical work13691286GLM 4.7 Flash
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
MMLU ProNot measured69.6%Only Llama 4 Scout measured
LegalBench (Vals AI)Not measured72.0%Only Llama 4 Scout measured
CorpFin (Vals AI)Not measured46.8%Only Llama 4 Scout measured
TaxEval (Vals AI)Not measured55.2%Only Llama 4 Scout measured
MortgageTax (Vals AI)Not measured57.8%Only Llama 4 Scout measured
MedQA (Vals AI)Not measured50.9%Only Llama 4 Scout measured
MedCode (Vals AI)Not measured23.3%Only Llama 4 Scout measured
MMLU Pro (Artificial Analysis run)Not measured75.2%Only Llama 4 Scout measured
LMArena Text: science13581278GLM 4.7 Flash
LMArena Text: medicine and healthcare13431275GLM 4.7 Flash
LMArena Text: legal and government13571285GLM 4.7 Flash
LMArena Text: business and finance13431257GLM 4.7 Flash
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 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
Design Arena: websites1194750GLM 4.7 Flash
Design Arena: UI components1205765GLM 4.7 Flash
Design Arena: game dev1134772GLM 4.7 Flash
Design Arena: data viz1123896GLM 4.7 Flash
Design Arena: 3D1120Not measuredOnly GLM 4.7 Flash measured
Design Arena: all code categories1177789GLM 4.7 Flash
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 index180
General benchmarks for GLM 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 4 ScoutLeader
SAGE (Vals AI)Not measured34.8%Only Llama 4 Scout measured
MedScribe (Vals AI)Not measured50.6%Only Llama 4 Scout measured
IFBench60.8%39.5%GLM 4.7 Flash
Long context reasoning (AA-LCR)41.7%27.7%GLM 4.7 Flash
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 Text13511279GLM 4.7 Flash
LMArena Text: instruction following13271248GLM 4.7 Flash
LMArena Text: creative writing12961249GLM 4.7 Flash
LMArena VisionNot measured1118Only Llama 4 Scout measured
LMArena Text: English13731304GLM 4.7 Flash
LMArena Text: non-English13301252GLM 4.7 Flash
LMArena Text: Chinese14031255GLM 4.7 Flash
LMArena Text: German13361273GLM 4.7 Flash
LMArena Text: JapaneseNot measured1206Only Llama 4 Scout measured
LMArena Text: Korean12831207GLM 4.7 Flash
LMArena Text: French13321283GLM 4.7 Flash
LMArena Text: Spanish13501278GLM 4.7 Flash
LMArena Text: Russian13331263GLM 4.7 Flash
LMArena Text: Polish12911265GLM 4.7 Flash
LMArena Text: multi-turn13421280GLM 4.7 Flash
LMArena Text: longer queries13451265GLM 4.7 Flash
LMArena Text: writing and language13201269GLM 4.7 Flash
LMArena Text: entertainment and media13041242GLM 4.7 Flash
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 4.7 Flash and Llama 4 Scout
BenchmarkGLM 4.7 FlashLlama 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 4.7 Flash$0.0003Fits in one request
Llama 4 Scout$0.0004Fits 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
Llama 4 Scout$0.010Fits 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
Llama 4 Scout$0.040Fits 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 Llama 4 Scout
SpecificationZ.ai GLM 4.7 FlashMeta Llama 4 Scout
MakerZ.aiMeta Llama
WeightsOpen weightsOpen weights
ReleasedJanuary 19, 2026April 5, 2025
Context window200K1.31M
Input $/Mtok$0.0653$0.175
Output $/Mtok$0.40$0.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computable$1.276
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than Llama 4 Scout for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and work measured by GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, GLM 4.7 Flash or Llama 4 Scout?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 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 4.7 Flash or Llama 4 Scout?

Llama 4 Scout, with 1.31M tokens against 200K.

How many benchmarks is the GLM 4.7 Flash vs Llama 4 Scout comparison based on?

41 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 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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