โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Llama 4 Scout vs Muse Spark 1.1

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Llama 4 Scout and Muse Spark 1.1.

Meta

Llama 4 Scout

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

View Full Specs
Meta

Muse Spark 1.1

Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context...

View Full Specs

Technical Specifications

SpecificationLlama 4 ScoutMuse Spark 1.1
ProviderMetaMeta
Context Window10,000,000 tokens1,048,576 tokens
Agent Suitability82/100N/A
Time to First Token (TTFT)350 msN/A
Deployment Modelself hostablemanaged api
Production Stabilitybetabeta
API AvailableYesYes
Released Date2025-04-052026-07-16

API Pricing Comparison

Input Price per Million Tokens

Llama 4 Scout

$0.10

Muse Spark 1.1

$1.25

Output Price per Million Tokens

Llama 4 Scout

$0.30

Muse Spark 1.1

$4.25

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8720.0%vsN/A
Llama 4 Scout
Muse Spark 1.1
HumanEvalPython coding & logic synthesis
8950.0%vsN/A
Llama 4 Scout
Muse Spark 1.1
MATHComplex mathematical problem solving
8100.0%vsN/A
Llama 4 Scout
Muse Spark 1.1
GPQAGraduate-level expert reasoning
6680.0%vsN/A
Llama 4 Scout
Muse Spark 1.1
HellaSwagCommonsense reasoning and inference
9450.0%vsN/A
Llama 4 Scout
Muse Spark 1.1
MT-BenchMulti-turn conversation flow quality
910.0%vsN/A
Llama 4 Scout
Muse Spark 1.1

Llama 4 Scout Quirks & Gotchas

  • โ–ธ10M context causes significant VRAM pressure โ€” recommend 4-bit quantization
  • โ–ธPrimarily designed for RAG, not agentic tool calling

Muse Spark 1.1 Quirks & Gotchas

No developer gotchas reported.