Llama 4 Scout vs Muse Spark 1.2

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60#215

meta

81#84

Signal-by-Signal Comparison

Signal	Llama 4 Scout	Delta	Muse Spark 1.2
Capabilities	67	-33	100
Benchmarks	59	+59	0
Pricing	100	+4	96
Context window size	97	+2	96
Recency	35	-65	100
Output Capacity	67	-28	96
Overall Result	3 wins	of 6	3 wins

It's a tie - both models win 3 signals each

Score History

Score History (32 data points)

Llama 4 ScoutMuse Spark 1.2

Llama 4 Scout

60.2

current score

Leader

Muse Spark 1.2

right now

Muse Spark 1.2

80.9

current score

LMMarketCap.com

Interactive Price Comparison

Quick presets

Monthly API calls

100Kcalls/month

Avg. input tokens/call

1,000tokens (~1,333 chars)

Avg. output tokens/call

500tokens (~667 chars)

Llama 4 Scout

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Best Value

Per request$0.000250

Daily$0.83

Monthly$25.00

Annual$300.00

Muse Spark 1.2

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Per request$0.003375

Daily$11.25

Monthly$337.50

Annual$4050.00

Llama 4 Scout saves you $312.50/month

That's $3750.00/year compared to Muse Spark 1.2 at your current usage level of 100K calls/month.

93% cheaper

Choose Llama 4 Scout for cost optimization

Llama 4 Scout pricing:

Input:$0.10/M tokens

Output:$0.30/M tokens

Muse Spark 1.2 pricing:

Input:$1.25/M tokens

Output:$4.25/M tokens

Llama 4 Scout

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Composite Score

Winner

Muse Spark 1.2

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Composite Score

Signal-by-Signal Comparison

Metric	Llama 4 Scout	Muse Spark 1.2	Winner
Overall Score	60	81	Muse Spark 1.2
Rank	#215	#84	Muse Spark 1.2
Quality Rank	#215	#84	Muse Spark 1.2
Adoption Rank	#215	#84	Muse Spark 1.2
Parameters	--	--	--
Context Window	1311K	1049K	Llama 4 Scout
Pricing	$0.10/$0.30/M	$1.25/$4.25/M	--
Signal Scores
Capabilities	67	100	Muse Spark 1.2
Benchmarks	59	--	Llama 4 Scout
Pricing	100	96	Llama 4 Scout
Context window size	97	96	Llama 4 Scout
Recency	35	100	Muse Spark 1.2
Output Capacity	67	96	Muse Spark 1.2

Benchmark Head-to-Head(7 benchmarks)

Llama 4: 0Muse Spark: 0

Llama 4

Muse Spark

Normalized 0-100%

MMLU

79.6%-

MMLU-Pro

74.3%-

GPQA Diamond

57.2%-

MATH-500

50.3%-

HumanEval

74.1%-

BBH

76%-

BigCodeBench

16.9%-

Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Llama 4 ScoutCompetitive

Scores 60/100 (rank #215), placing it in the top 26% of all 290 models tracked.

Raw Quality0/100

Cost Efficiency0/100

Speed0/100

Muse Spark 1.2Strong Performer

Scores 81/100 (rank #84), placing it in the top 71% of all 290 models tracked.

Raw Quality0/100

Cost Efficiency0/100

Speed0/100

Muse Spark 1.2 has a 21-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.

When to Use Each Model

Choose Llama 4 Scout when you need:

High-volume production workloads where API costs must be minimized
Self-hosted deployments where you need full control over the model

Choose Muse Spark 1.2 when you need:

Step-by-step reasoning and chain-of-thought problem solving

Cost-Performance Analysis

Llama 4 ScoutBest Value

Input cost$0.10/M tokens

Output cost$0.30/M tokens

Cost per quality point$0.007

Est. monthly (1M tokens/day)$6.00

Muse Spark 1.2

Input cost$1.25/M tokens

Output cost$4.25/M tokens

Cost per quality point$0.068

Est. monthly (1M tokens/day)$82.50

Llama 4 Scout offers 93% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Llama 4 Scout vs $82.50/month with Muse Spark 1.2 - a $76.50 monthly difference.

Latency & Speed

Llama 4 ScoutFaster

Speed score0/100

Muse Spark 1.2

Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Llama 4 Scout

Customer support chatbot

Suitable for user-facing chat with competitive response times. Llama 4 Scout also offers lower per-token costs for high-volume support

Llama 4 Scout

Long document analysis

Larger context window (1311K tokens) can process longer documents, contracts, and research papers in a single pass

Llama 4 Scout

Batch data extraction

Lower output pricing ($0.30/M) reduces costs when processing thousands of records daily

Llama 4 Scout

Creative writing & content

Higher overall composite score (81/100) correlates with better nuance, coherence, and style in long-form content

Muse Spark 1.2

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

Llama 4 Scout

Which Should You Choose?

Our recommendation:

Muse Spark 1.2

Muse Spark 1.2 clearly outperforms Llama 4 Scout with a significant 20.700000000000003-point lead. For most general use cases, Muse Spark 1.2 is the stronger choice. However, Llama 4 Scout may still excel in niche scenarios.

By Use Case

Best for Quality

Llama 4 Scout

Marginally better benchmark scores; both are excellent

Best for Cost

Llama 4 Scout

93% lower pricing; better value at scale

Best for Reliability

Llama 4 Scout

Higher uptime and faster response speeds

Best for Prototyping

Llama 4 Scout

Stronger community support and better developer experience

Best for Production

Llama 4 Scout

Wider enterprise adoption and proven at scale

Llama 4 Scout

by Meta

Choose for Quality - Marginally better benchmark scores; both are excellent
Choose for Cost - 93% lower pricing; better value at scale
Choose for Reliability - Higher uptime and faster response speeds
Choose for Prototyping - Stronger community support and better developer experience
Choose for Production - Wider enterprise adoption and proven at scale