Muse Glimmer 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 Muse Glimmer when a specific cost or latency profile matters more than the latest capabilities.
Muse Glimmer 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. Muse Glimmer is meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. 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: Muse Spark Open holds 7.6× more — 1M tokens (~1,500 pages) vs 128K (~197 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 2 months (released October 15, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Muse Glimmer | Muse Spark Open |
|---|---|---|
| Provider | Meta (US) | Meta (US) |
| Released | August 10, 2026 | October 15, 2026 |
| Context window | 128K (~197 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 | Not published | Not published |
Who wins what
Runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit
Muse Glimmer
Muse Glimmer lists runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit among its strengths; Muse Spark Open does not.
Open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine
Muse Glimmer
Muse Glimmer lists open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine among its strengths; Muse Spark Open does not.
Agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery
Muse Glimmer
Muse Glimmer lists agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery 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
Muse Glimmer is comparatively weak here — a distilled ~30B model - ceiling below its closed teacher (Muse Spark) and cloud flagships
Artificial Analysis Intelligence Index of 39, first among US open-weight models
Muse Spark Open
Muse Glimmer is comparatively weak here — no independent Artificial Analysis intelligence score published yet
About 143 output tokens/sec; up to 128K output tokens
Muse Spark Open
Its 1M tokens window holds about 7.6× more than Muse Glimmer's 128K in a single prompt.
Largest single-prompt input
Muse Spark Open
Its 1M tokens window is about 7.6× larger than Muse Glimmer's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Muse Spark Open
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit
→ Muse Glimmer
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.
Muse Glimmer: where it fits
Meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. Released August 10, 2026 by Meta, it is built for runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit, open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine, agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery, and 128K context, text and image input, trained on 100+ languages.
Its trade-offs are real: a distilled ~30B model - ceiling below its closed teacher (Muse Spark) and cloud flagships, no independent Artificial Analysis intelligence score published yet, published benchmarks (e.g. SWE-Bench Verified 76.0) are Meta's own, and 4-bit quantization to fit consumer GPUs trades away some accuracy. 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 Muse Glimmer 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 Muse Glimmer 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, Muse Glimmer leans toward runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit 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, Muse Glimmer or Muse Spark Open?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Muse Spark Open — 1M tokens vs 128K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from Muse Glimmer 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, Muse Glimmer or Muse Spark Open?
Muse Spark Open — released October 15, 2026, about 2 months after Muse Glimmer.
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.