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Llama 4 Scout vs Muse Spark 1.3

Updated October 21, 2026. 52 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Llama 4 ScoutMeta Llama
Coding
9.1
Overall
6.5
Output $/M
$0.30
0
Muse Spark 1.3Meta
Coding
79.7
Overall
48.1
Output $/M
$4.25
52
vs boards won of 52 shared

Decision reading

Pick Muse Spark 1.3 for coding: it scores 79.7 on the Vibe Coding Index against 9.1 for Llama 4 Scout.

Pick Llama 4 Scout when output tokens cost 14.2x less, or when the context window is larger, 1.31M against 1.05M tokens.

Shared results
52
Llama 4 Scout only
28
Muse Spark 1.3 only
40
Like-for-like categories
8 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
Llama 4 Scout 9.1 from 1 benchmark, Muse Spark 1.3 79.7 from 2 benchmarks.
Widest category
Web design, 68.9 points apart on average over 5 shared benchmarks.
Widest single gap
OTIS Mock AIME: Llama 4 Scout 7.8% against Muse Spark 1.3 99.2%, 91.4 points apart on a 0 to 100 scale.
Output price
Llama 4 Scout $0.30 against Muse Spark 1.3 $4.25 per million output tokens, 14.2x apart.
Context window
Llama 4 Scout takes 1.31M tokens, Muse Spark 1.3 1.05M.

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
CategoryLlama 4 ScoutBarsMuse Spark 1.3Ties
Coding04
Intelligence02
Agentic work01
Reasoning07
Math03
Knowledge04
Web design05
General026
All shared boards052
CodingLike-for-likeFour of these boards feed the Vibe Coding Index04
Coding benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
SWE-bench Verified9.1%Not measuredOnly Llama 4 Scout measured
LiveBench codingNot measured90.2%Only Muse Spark 1.3 measured
LMArena WebDevNot measured1659Only Muse Spark 1.3 measured
AA Coding Index8.275.8Muse Spark 1.3
LiveCodeBench (Vals AI)38.5%Not measuredOnly Llama 4 Scout measured
Terminal-Bench 4 (Vals AI)Not measured10.6%Only Muse Spark 1.3 measured
Vibe Code Bench (Vals AI)Not measured82.9%Only Muse Spark 1.3 measured
Code migration (Vals AI)Not measured27.6%Only Muse Spark 1.3 measured
ProgramBench (Vals AI)Not measured0.5%Only Muse Spark 1.3 measured
IOI (Vals AI)Not measured43.9%Only Muse Spark 1.3 measured
Terminal-Bench 2.1 (Vals AI)Not measured72.3%Only Muse Spark 1.3 measured
CyberBench (Vals AI)Not measured69.4%Only Muse Spark 1.3 measured
LiveCodeBench (Artificial Analysis run)29.9%Not measuredOnly Llama 4 Scout measured
SciCode21.3%59.7%Muse Spark 1.3
Terminal-Bench Hard (Artificial Analysis run)1.5%Not measuredOnly Llama 4 Scout measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
ALE-BenchNot measured1688.3Only Muse Spark 1.3 measured
LMArena Text: coding12861510Muse Spark 1.3
LMArena Text: software and IT12861511Muse Spark 1.3
LMArena WebDev: ReactNot measured1672Only Muse Spark 1.3 measured
LMArena WebDev: HTMLNot measured1653Only Muse Spark 1.3 measured
LMArena WebDev: from an imageNot measured1640Only Muse Spark 1.3 measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
AA Intelligence Index6.548.1Muse Spark 1.3
Epoch Capabilities Index129.6157.2Muse Spark 1.3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
AA Agentic Index0.555.5Muse Spark 1.3
Design Arena: agents building web appsNot measured1297Only Muse Spark 1.3 measured
Design Arena: agents building full-stack appsNot measured1295Only Muse Spark 1.3 measured
Design Arena: agents building mobile appsNot measured1217Only Muse Spark 1.3 measured
Design Arena: agents building Godot gamesNot measured1241Only Muse Spark 1.3 measured
Design Arena: PowerPoint slidesNot measured1244Only Muse Spark 1.3 measured
Design Arena: spreadsheetsNot measured1048Only Muse Spark 1.3 measured
LiveBench researchNot measured68.6%Only Muse Spark 1.3 measured
LiveBench browserNot measured80.0%Only Muse Spark 1.3 measured
LiveBench long agenticNot measured40.4%Only Muse Spark 1.3 measured
Finance Agent (Vals AI)Not measured58.9%Only Muse Spark 1.3 measured
Tax Agent Bench (Vals AI)Not measured36.0%Only Muse Spark 1.3 measured
Legal Research Bench (Vals AI)Not measured40.9%Only Muse Spark 1.3 measured
Excel Modeling Benchmark (Vals AI)Not measured62.7%Only Muse Spark 1.3 measured
Terminal-Bench-Science (Vals AI)Not measured4.3%Only Muse Spark 1.3 measured
τ²-Bench Telecom15.5%Not measuredOnly Llama 4 Scout measured
APEX-AgentsNot measured58.6%Only Muse Spark 1.3 measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
GPQA Diamond47.0%Not measuredOnly Llama 4 Scout measured
LiveBench reasoningNot measured89.7%Only Muse Spark 1.3 measured
MMMU Pro (Vals AI)58.8%Not measuredOnly Llama 4 Scout measured
GPQA Diamond (Artificial Analysis run)58.7%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)3.8%48.7%Muse Spark 1.3
GPQA Diamond (Epoch AI run)51.8%Not measuredOnly Llama 4 Scout measured
ARC-AGI0.5%Not measuredOnly Llama 4 Scout measured
ARC-AGI-20.0%Not measuredOnly Llama 4 Scout measured
Chess puzzlesNot measured37.0%Only Muse Spark 1.3 measured
Mystery game puzzlesNot measured25.0%Only Muse Spark 1.3 measured
LMArena Text: hard prompts12661503Muse Spark 1.3
LMArena Text: expert12351519Muse Spark 1.3
LMArena Text: hard prompts in English12931500Muse Spark 1.3
LMArena Vision: diagrams11251330Muse Spark 1.3
LMArena Vision: homework11481296Muse Spark 1.3
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
AIME19.0%Not measuredOnly Llama 4 Scout measured
MATH 500 (Vals AI)79.2%Not measuredOnly Llama 4 Scout measured
MGSM (Vals AI)88.0%Not measuredOnly Llama 4 Scout measured
AA Math Index14.0Not measuredOnly Llama 4 Scout measured
AIME 2025 (Artificial Analysis run)14.0%Not measuredOnly Llama 4 Scout measured
OTIS Mock AIME7.8%99.2%Muse Spark 1.3
FrontierMath, tiers 1 to 3Not measured74.4%Only Muse Spark 1.3 measured
FrontierMath, tier 4Not measured46.3%Only Muse Spark 1.3 measured
ProofBenchNot measured58.0%Only Muse Spark 1.3 measured
MATH level 562.3%Not measuredOnly Llama 4 Scout measured
LMArena Text: math12871497Muse Spark 1.3
LMArena Text: mathematical work12861491Muse Spark 1.3
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
MMLU Pro69.6%Not measuredOnly Llama 4 Scout measured
LegalBench (Vals AI)72.0%Not measuredOnly Llama 4 Scout measured
CorpFin (Vals AI)46.8%Not measuredOnly Llama 4 Scout measured
TaxEval (Vals AI)55.2%Not measuredOnly Llama 4 Scout measured
MortgageTax (Vals AI)57.8%Not measuredOnly Llama 4 Scout measured
MedQA (Vals AI)50.9%Not measuredOnly Llama 4 Scout measured
MedCode (Vals AI)23.3%Not measuredOnly Llama 4 Scout measured
MMLU Pro (Artificial Analysis run)75.2%Not measuredOnly Llama 4 Scout measured
LMArena Text: science12781507Muse Spark 1.3
LMArena Text: medicine and healthcare12751493Muse Spark 1.3
LMArena Text: legal and government12851499Muse Spark 1.3
LMArena Text: business and finance12571490Muse Spark 1.3
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index05
Web design benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
Design Arena: websites7501356Muse Spark 1.3
Design Arena: UI components7671352Muse Spark 1.3
Design Arena: game dev7731329Muse Spark 1.3
Design Arena: data viz8961343Muse Spark 1.3
Design Arena: 3DNot measured1359Only Muse Spark 1.3 measured
Design Arena: all code categories7901353Muse Spark 1.3
Design Arena: SVGNot measured1300Only Muse Spark 1.3 measured
Design Arena: ASCII artNot measured1280Only Muse Spark 1.3 measured
LiveBench designNot measured74.8%Only Muse Spark 1.3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index026
General benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
LiveBench data analysisNot measured79.6%Only Muse Spark 1.3 measured
SAGE (Vals AI)34.8%Not measuredOnly Llama 4 Scout measured
MedScribe (Vals AI)50.6%Not measuredOnly Llama 4 Scout measured
IFBench39.5%Not measuredOnly Llama 4 Scout measured
Long context reasoning (AA-LCR)27.7%83.0%Muse Spark 1.3
DTBench57.9%96.5%Muse Spark 1.3
LMCA12.0%53.9%Muse Spark 1.3
Fiction.LiveBench36.0%Not measuredOnly Llama 4 Scout measured
LMArena Text12791490Muse Spark 1.3
LMArena Text: instruction following12481479Muse Spark 1.3
LMArena Text: creative writing12491462Muse Spark 1.3
LMArena Vision11181308Muse Spark 1.3
LMArena Text: English13041495Muse Spark 1.3
LMArena Text: non-English12521481Muse Spark 1.3
LMArena Text: Chinese12551532Muse Spark 1.3
LMArena Text: German12731513Muse Spark 1.3
LMArena Text: Japanese12061470Muse Spark 1.3
LMArena Text: Korean12071490Muse Spark 1.3
LMArena Text: French12831511Muse Spark 1.3
LMArena Text: Spanish12781496Muse Spark 1.3
LMArena Text: Russian12631491Muse Spark 1.3
LMArena Text: Polish12651490Muse Spark 1.3
LMArena Text: multi-turn12801487Muse Spark 1.3
LMArena Text: longer queries12651488Muse Spark 1.3
LMArena Text: writing and language12691470Muse Spark 1.3
LMArena Text: entertainment and media12421457Muse Spark 1.3
LMArena Vision: English11431298Muse Spark 1.3
LMArena Vision: Chinese11061384Muse Spark 1.3
LMArena Vision: reading text11171319Muse Spark 1.3
LMArena Vision: humor11021293Muse Spark 1.3
LMArena Vision: creative writing11261296Muse Spark 1.3
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Llama 4 Scout and Muse Spark 1.3
BenchmarkLlama 4 ScoutMuse Spark 1.3Leader
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

Llama 4 Scout$0.0003Fits in one request
Muse Spark 1.3$0.0034Fits in one request

Llama 4 Scout costs less

Repository review

50K input + 3K output tokens

Llama 4 Scout$0.0059Fits in one request
Muse Spark 1.3$0.075Fits in one request

Llama 4 Scout costs less

Agent loop

200K input + 10K output tokens

Llama 4 Scout$0.023Fits in one request
Muse Spark 1.3$0.292Fits 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 Llama 4 Scout and Muse Spark 1.3
SpecificationMeta Llama 4 ScoutMeta Muse Spark 1.3
MakerMeta LlamaMeta
WeightsOpen weightsNo public weights listed
ReleasedApril 5, 2025September 2, 2026
Context window1.31M1.05M
Input $/Mtok$0.10$1.25
Output $/Mtok$0.30$4.25
Coding index9.179.7
Independent measurements behind it12
Cost per solved task$1.276Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 4 Scout better than Muse Spark 1.3 for coding?

Pick Muse Spark 1.3 for coding: it scores 79.7 on the Vibe Coding Index against 9.1 for Llama 4 Scout. Pick Llama 4 Scout when output tokens cost 14.2x less, or when the context window is larger, 1.31M against 1.05M tokens.

Which is cheaper, Llama 4 Scout or Muse Spark 1.3?

Llama 4 Scout costs $0.10 per million input tokens and $0.30 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for Llama 4 Scout only.

Which has the bigger context window, Llama 4 Scout or Muse Spark 1.3?

Llama 4 Scout, with 1.31M tokens against 1.05M.

How many benchmarks is the Llama 4 Scout vs Muse Spark 1.3 comparison based on?

52 benchmarks have a result for both models as of October 21, 2026. Llama 4 Scout's coding index rests on 1 independent benchmark and Muse Spark 1.3's on 2. Where only one model has a result, the page says so instead of naming a winner.

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