Llama 4 Scout vs Muse Spark 1.3 Contributor
| Signal | Llama 4 Scout | Delta | Muse Spark 1.3 Contributor |
|---|---|---|---|
Capabilities | 67 | -33 | |
Benchmarks | 59 | +59 | |
Pricing | 100 | 0 | |
Context window size | 97 | +2 | |
Recency | 35 | -65 | |
Output Capacity | 67 | -28 | |
| Overall Result | 2 wins | of 6 | 4 wins |
Score History
60.2
current score
Llama 4 Scout
right now
40
current score
Llama 4 Scout
Meta
Muse Spark 1.3 Contributor
meta
Muse Spark 1.3 Contributor saves you $5.00/month
That's $60.00/year compared to Llama 4 Scout at your current usage level of 100K calls/month.
| Metric | Llama 4 Scout | Muse Spark 1.3 Contributor | Winner |
|---|---|---|---|
| Overall Score | 60 | 40 | Llama 4 Scout |
| Rank | #215 | #264 | Llama 4 Scout |
| Quality Rank | #215 | #264 | Llama 4 Scout |
| Adoption Rank | #215 | #264 | Llama 4 Scout |
| Parameters | -- | -- | -- |
| Context Window | 1311K | 1049K | Llama 4 Scout |
| Pricing | $0.10/$0.30/M | $0.10/$0.20/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 100 | Muse Spark 1.3 Contributor |
| Benchmarks | 59 | -- | Llama 4 Scout |
| Pricing | 100 | 100 | Muse Spark 1.3 Contributor |
| Context window size | 97 | 96 | Llama 4 Scout |
| Recency | 35 | 100 | Muse Spark 1.3 Contributor |
| Output Capacity | 67 | 96 | Muse Spark 1.3 Contributor |
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.
Scores 60/100 (rank #215), placing it in the top 26% of all 290 models tracked.
Scores 40/100 (rank #264), placing it in the top 9% of all 290 models tracked.
Llama 4 Scout has a 20-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Choose Llama 4 Scout when you need:
- Self-hosted deployments where you need full control over the model
Choose Muse Spark 1.3 Contributor when you need:
- High-volume production workloads where API costs must be minimized
- Step-by-step reasoning and chain-of-thought problem solving
Llama 4 Scout offers 25% better value per quality point. At 1M tokens/day, you'd spend $4.50/month with Muse Spark 1.3 Contributor vs $6.00/month with Llama 4 Scout - a $1.50 monthly difference.
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.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Muse Spark 1.3 Contributor also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1311K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.20/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (60/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Llama 4 Scout clearly outperforms Muse Spark 1.3 Contributor with a significant 20.200000000000003-point lead. For most general use cases, Llama 4 Scout is the stronger choice. However, Muse Spark 1.3 Contributor 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
Muse Spark 1.3 Contributor
25% 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
by Meta
- Choose for Quality - Marginally better benchmark scores; both are excellent
- 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
| Capability | Llama 4 Scout | Muse Spark 1.3 Contributor |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
Llama 4 Scout
Meta
Muse Spark 1.3 Contributor
meta
Muse Spark 1.3 Contributor saves you $0.1200/month
That's 22% cheaper than Llama 4 Scout at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Llama 4 Scout | Muse Spark 1.3 Contributor |
|---|---|---|
| Context Window | 1.3M | 1.0M |
| Max Output Tokens | 16,384 | 943,718 |
| Open Source | Yes | No |
| Created | Apr 5, 2025 | Sep 2, 2026 |