Muse Glimmer vs Muse Wonder 1.0
Meta · US | Meta · US · Updated June 2026
Quick verdict
Both are Meta models. Muse Wonder 1.0 is the newer, generally stronger default; reach for Muse Glimmer when its lower price or a specific cost or latency profile matters more than the latest capabilities.
Muse Glimmer and Muse Wonder 1.0 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 Wonder 1.0 is meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window. 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
- ▸Cost model: Muse Glimmer ships open weights you can self-host (hardware cost only, no per-token fee), while Muse Wonder 1.0 is API-metered at $4/$20 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: Muse Wonder 1.0 holds 8× more — 1M tokens (~1,573 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 Wonder 1.0 is the newer model by about 2 months (released October 12, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Muse Glimmer | Muse Wonder 1.0 |
|---|---|---|
| Provider | Meta (US) | Meta (US) |
| Released | August 10, 2026 | October 12, 2026 |
| Context window | 128K (~197 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | Open weight (self-host / free) | $4/$20 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, image, code | text, image, video, audio |
| 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
Open weights make this possible at all — Muse Wonder 1.0 is API-only, so it cannot leave the vendor's servers.
Open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine
Muse Glimmer
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 — and its weights are open while Muse Wonder 1.0 is API-only.
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 Wonder 1.0 does not.
Meta Superintelligence Labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused Muse Spark family
Muse Wonder 1.0
Muse Glimmer is comparatively weak here — a distilled ~30B model - ceiling below its closed teacher (Muse Spark) and cloud flagships
Artificial Analysis Intelligence Index score of 52 (a gated 'Wonder Full' subscription variant scores 56, tied with Claude Sonnet 5.5, behind only Opus 5.5 at 58)
Muse Wonder 1.0
Muse Glimmer is comparatively weak here — no independent Artificial Analysis intelligence score published yet
78.8% on DeepSWE v1.1 long-horizon coding, ahead of both Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%)
Muse Wonder 1.0
Its 1M tokens window holds about 8× more than Muse Glimmer's 128K in a single prompt.
Lowest cost at scale
Muse Glimmer
Its weights are open, so at volume you pay for your own hardware instead of Muse Wonder 1.0's $4/$20 per 1M tokens.
Largest single-prompt input
Muse Wonder 1.0
Its 1M tokens window is about 8× larger than Muse Glimmer's 128K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Muse Glimmer
At Open weight (self-host / free) it undercuts Muse Wonder 1.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Wonder 1.0
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Muse Glimmer
Open weights let you run it on your own hardware; Muse Wonder 1.0 is API-only.
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 superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family
→ Muse Wonder 1.0
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 Wonder 1.0: where it fits
Meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window. Released October 12, 2026 by Meta, it is built for meta Superintelligence Labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused Muse Spark family, artificial Analysis Intelligence Index score of 52 (a gated 'Wonder Full' subscription variant scores 56, tied with Claude Sonnet 5.5, behind only Opus 5.5 at 58), 78.8% on DeepSWE v1.1 long-horizon coding, ahead of both Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%), and accepts text, image, video, audio, and PDF input against a 1,048,576-token context window.
Its trade-offs: the stronger 'Wonder Full' variant is gated behind $50/$200-per-month Muse Code subscriptions, with no public API or independently verifiable pricing, meta's full safety report had not been published as of launch, first release in a brand-new model family — no track record yet next to Meta's more established Muse Spark line, and benchmark comparisons against Opus 5.5 and GPT-6 Astra are Meta's own self-reported figures. At $4 in / $20 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Because Muse Glimmer and Muse Wonder 1.0 come from the same lab (Meta), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Muse Wonder 1.0 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 Wonder 1.0 and drop down only with a concrete reason.
Want both Muse Glimmer and Muse Wonder 1.0 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is Muse Glimmer or Muse Wonder 1.0 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 Wonder 1.0 leans toward meta superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Glimmer or Muse Wonder 1.0?
Muse Glimmer is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Wonder 1.0 is API-metered at $4/$20 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Muse Wonder 1.0 — 1M tokens vs 128K, about 8× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from Muse Glimmer to Muse Wonder 1.0?
Since both are Meta models, the newer one (Muse Wonder 1.0) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Muse Glimmer or Muse Wonder 1.0?
Muse Wonder 1.0 — released October 12, 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.