Llama 4 Maverick vs Muse Spark 1.3
Meta · US | Meta · US · Updated June 2026
Quick verdict
Both are Meta models. Muse Spark 1.3 is the newer, generally stronger default; reach for Llama 4 Maverick when its lower price or a specific cost or latency profile matters more than the latest capabilities.
Llama 4 Maverick and Muse Spark 1.3 are both Meta models, so the real question is not which lab to trust but which tier fits your workload and budget. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. 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. 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: Llama 4 Maverick 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 (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Muse Spark 1.3 is the newer model by about 17 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Llama 4 Maverick | Muse Spark 1.3 |
|---|---|---|
| Provider | Meta (US) | Meta (US) |
| Released | April 2025 | September 2, 2026 |
| Context window | 1M (~1,500 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | Open weight (self-host / free) | $1.25/$4.25 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, image, code | text, image, video |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | 98.1% |
Who wins what
Open weights, 1M context
Llama 4 Maverick
Open weights make this possible at all — Muse Spark 1.3 is API-only, so it cannot leave the vendor's servers.
Strong image + text understanding
Llama 4 Maverick
Muse Spark 1.3 is comparatively weak here — strongest 'max' reasoning configuration still gated pending additional safety testing
Self-hostable
Llama 4 Maverick
Meta's open-weight 1M-context multimodal model for self-hosted deployments — and its weights are open while Muse Spark 1.3 is API-only.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
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 — and it is the newer of the two.
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; Llama 4 Maverick 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; Llama 4 Maverick does not.
Lowest cost at scale
Llama 4 Maverick
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
→ Llama 4 Maverick
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
→ Llama 4 Maverick
Open weights let you run it on your own hardware; Muse Spark 1.3 is API-only.
Anyone whose priority is open weights, 1m context
→ Llama 4 Maverick
It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
That is its strongest area.
Llama 4 Maverick: where it fits
Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.
Its trade-offs are real: needs serious hardware to self-host, and trails closed frontier on reasoning. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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: 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.
The bottom line for this matchup
Because Llama 4 Maverick and Muse Spark 1.3 come from the same lab (Meta), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Muse Spark 1.3 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 1.3 and drop down only with a concrete reason.
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See pricingFrequently asked questions
Is Llama 4 Maverick or Muse Spark 1.3 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 Maverick leans toward open weights, 1m context while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Llama 4 Maverick or Muse Spark 1.3?
Llama 4 Maverick 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 (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Llama 4 Maverick to Muse Spark 1.3?
Since both are Meta models, the newer one (Muse Spark 1.3) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Llama 4 Maverick or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 17 months after Llama 4 Maverick.
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.