Muse Spark 1.3 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 Spark 1.3 when a specific cost or latency profile matters more than the latest capabilities.
Muse Spark 1.3 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 Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. 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
- ▸Cost model: Muse Spark Open ships open weights you can self-host (hardware cost only, no per-token fee), while Muse Spark 1.3 is API-metered at $1.25/$4.25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Muse Spark Open is the newer model by about 43 days (released October 15, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Muse Spark 1.3 | Muse Spark Open |
|---|---|---|
| Provider | Meta (US) | Meta (US) |
| Released | September 2, 2026 | October 15, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $1.25/$4.25 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, video | text, image, video, audio, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | 98.1% | Not published |
Who wins what
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Muse Spark 1.3 lists agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2 among its strengths; Muse Spark Open does not.
DeepSWE v1.1 long-horizon software engineering (75.4)
Muse Spark 1.3
Muse Spark 1.3 lists deepSWE v1.1 long-horizon software engineering (75.4) among its strengths; Muse Spark Open does not.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1)
Muse Spark 1.3
Muse Spark 1.3 lists near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1) 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
Open weights make this possible at all — Muse Spark 1.3 is API-only, so it cannot leave the vendor's servers.
Artificial Analysis Intelligence Index of 39, first among US open-weight models
Muse Spark Open
Muse Spark 1.3 is comparatively weak here — not yet open-weight, despite Meta roadmapping a future Muse Spark weights release
About 143 output tokens/sec; up to 128K output tokens
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 its weights are open while Muse Spark 1.3 is API-only.
Lowest cost at scale
Muse Spark Open
Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Muse Spark Open
At Open weight (self-host / free) it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ Muse Spark Open
Open weights let you run it on your own hardware; Muse Spark 1.3 is API-only.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
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 Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs are real: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
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 Spark 1.3 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 Spark 1.3 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 Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 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 Spark 1.3 or Muse Spark Open?
Muse Spark Open is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Spark 1.3 is API-metered at $1.25/$4.25 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?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Muse Spark 1.3 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 Spark 1.3 or Muse Spark Open?
Muse Spark Open — released October 15, 2026, about 43 days after Muse Spark 1.3.
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.