Llama 4 Scout vs Muse Spark Open
Meta · US | Meta · US · Updated June 2026
Quick verdict
Both are Meta models. Muse Spark Open is the newer, generally stronger default; reach for Llama 4 Scout when a specific cost or latency profile matters more than the latest capabilities.
Llama 4 Scout and Muse Spark Open are both Meta models, so the real question is not which lab to trust but which tier fits your workload and budget. Llama 4 Scout is the 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Muse Spark Open is meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
- ▸Context window: Llama 4 Scout holds 10× more — 10M (~15,000 pages) vs 1M tokens (~1,500 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Muse Spark Open is the newer model by about 19 months (released October 15, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Llama 4 Scout | Muse Spark Open |
|---|---|---|
| Provider | Meta (US) | Meta (US) |
| Released | April 2025 | October 15, 2026 |
| Context window | 10M (~15,000 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | Open weight (self-host / free) | Open weight (self-host / free) |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, image, code | text, image, video, audio, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | 15% | Not published |
Who wins what
Largest advertised context (10M)
Llama 4 Scout
Its 10M window holds about 10× more than Muse Spark Open's 1M tokens in a single prompt.
Open weights, single-GPU friendly
Llama 4 Scout
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller — and it carries the larger 10M context.
Self-hosted, data-private deployment
Llama 4 Scout
Llama 4 Scout lists self-hosted, data-private deployment among its strengths; Muse Spark Open does not.
Meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input
Muse Spark Open
Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License — and it is the newer of the two.
Artificial Analysis Intelligence Index of 39, first among US open-weight models
Muse Spark Open
Muse Spark Open lists artificial Analysis Intelligence Index of 39, first among US open-weight models among its strengths; Llama 4 Scout does not.
About 143 output tokens/sec; up to 128K output tokens
Muse Spark Open
Muse Spark Open lists about 143 output tokens/sec; up to 128K output tokens among its strengths; Llama 4 Scout does not.
Largest single-prompt input
Llama 4 Scout
Its 10M window is about 10× larger than Muse Spark Open's 1M tokens, fitting roughly 15,000 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Llama 4 Scout
Larger 10M window fits more in one prompt.
Anyone whose priority is largest advertised context (10m)
→ Llama 4 Scout
It is specifically built for that.
Anyone whose priority is meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input
→ Muse Spark Open
That is its strongest area.
Llama 4 Scout: where it fits
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Released April 2025 by Meta, it is built for largest advertised context (10M), open weights, single-GPU friendly, self-hosted, data-private deployment, and retrieval over very long inputs.
Its trade-offs are real: effective recall degrades far below 10M, and ~15% on long-context multi-needle reasoning. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
Muse Spark Open: where it fits
Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. Released October 15, 2026 by Meta, it is built for meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input, artificial Analysis Intelligence Index of 39, first among US open-weight models, and about 143 output tokens/sec; up to 128K output tokens.
Its trade-offs: weakest of the three Muse models (Wonder Full scores 56, Wonder 52), muse Model License: attribution required and a revenue threshold (reported as about $20M; check the license text) before a separate license is needed, and needs about 1 TB of memory at 4-bit; no first-party per-token price confirmed. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Because Llama 4 Scout and Muse Spark Open come from the same lab (Meta), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Muse Spark Open is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Muse Spark Open and drop down only with a concrete reason.
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See pricingFrequently asked questions
Is Llama 4 Scout or Muse Spark Open better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Llama 4 Scout leans toward largest advertised context (10m) while Muse Spark Open leans toward meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Llama 4 Scout or Muse Spark Open?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Llama 4 Scout — 10M vs 1M tokens, about 10× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from Llama 4 Scout to Muse Spark Open?
Since both are Meta models, the newer one (Muse Spark Open) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Llama 4 Scout or Muse Spark Open?
Muse Spark Open — released October 15, 2026, about 19 months after Llama 4 Scout.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.