AI model comparison
Muse Spark 1.3 Contributor vs Llama 4 Scout
Side by side comparison of Muse Spark 1.3 Contributor and Llama 4 Scout on pricing, benchmark scores, context window, and more.
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows.
- Input / 1M
- $0.10
- Output / 1M
- $0.20
- Context
- 1.05M
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.
- Input / 1M
- $0.10
- Output / 1M
- $0.30
- Context
- 1.31M
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Muse Spark 1.3 Contributor
1.2x cheaper for a typical chat
Higher intelligence score
Not available
Not enough benchmark data
Larger context window
Llama 4 Scout
1.31M vs 1.05M tokens
Newer release
Muse Spark 1.3 Contributor
Released September 2, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
Muse Spark 1.3 Contributor vs Llama 4 Scout API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.10 | $0.10 |
| Output tokensPer 1M tokens | $0.20 | $0.30 |
| Cached input (read)Per 1M tokens | $0.00 | Not available |
| Cache writePer 1M tokens | Not available | Not available |
| Web searchPer request | $0.0025 | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 1.05M tokens | 1.31M tokens |
| Max output | 944K tokens | 16K tokens |
| Input types | File, Image, Text, Video | Image, Text |
| Output types | Text | Text |
| Reasoning effort levels | Max, Extra high, High, Medium, Low, Minimal | Not available |
| Default reasoning effort | Medium | Not available |
| Release date | September 2, 2026 | April 5, 2025 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Not supported | Supported |
| Deterministic seed | Not supported | Supported |
| Verbosity control | Not supported | Not supported |
Our take
Muse Spark 1.3 Contributor is 1.2x cheaper for a typical chat. Llama 4 Scout has the larger context window (1.31M vs 1.05M tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Muse Spark 1.3 Contributor or Llama 4 Scout cheaper?
Muse Spark 1.3 Contributor is cheaper for a typical chat (2K input tokens and 500 output tokens). Muse Spark 1.3 Contributor costs $0.10 per 1M input tokens and $0.20 per 1M output tokens, while Llama 4 Scout costs $0.10 per 1M input tokens and $0.30 per 1M output tokens.
Which has a bigger context window, Muse Spark 1.3 Contributor or Llama 4 Scout?
Llama 4 Scout supports up to 1.31M tokens of context, compared with 1.05M for Muse Spark 1.3 Contributor.
Can I use Muse Spark 1.3 Contributor and Llama 4 Scout at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Muse Spark 1.3 Contributor and Llama 4 Scout answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Muse Spark 1.3 Contributor and Llama 4 Scout at the same time. Compare the answers side by side and keep the best one.