Meta: Muse Wonder vs ScaleDown: Summarize: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Muse Wonder (meta/muse-wonder) vs ScaleDown: Summarize (scaledown/summarize). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Muse Wonder (meta/muse-wonder) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Muse Wonder: Activate ephemeral prefix caching to slash input costs by 50% (down to $2/1M) or route via asynchronous Batch API for 50% off standard token rates.
ScaleDown: Summarize (scaledown/summarize) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for ScaleDown: Summarize: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.02/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Muse Wonder (API ID: meta/muse-wonder) vs ScaleDown: Summarize (API ID: scaledown/summarize), ScaleDown: Summarize offers lower standard input pricing at $0.04/1M tokens ($0/1M output), while ScaleDown: Summarize leads in cached prefix economics at $0.02/1M tokens (50% discount). Meta: Muse Wonder achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
Auto-discovered via live global telemetry registry.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | Meta: Muse Wonder | ScaleDown: Summarize | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta/muse-wonder | scaledown/summarize | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $4 / $20 | $0.04 / $0 | ScaleDown: Summarize |
| Cache Read Price (per 1M) | $2/1M (50% Off) | $0.02/1M (50% Off) | ScaleDown: Summarize |
| Context Window / Max Output | 1024K In / 922K Out | 977K In / 4K Out | Meta: Muse Wonder |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Muse Wonder (-0ms) |
Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and retu
Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source,
Real-Time Stack Cost & Hidden-Fee Simulator (MAU / Token / Egress / GMV)
Calibrated with Reddit r/FinOps & r/devops telemetry: Includes Context Caching, Bandwidth Egress, and MoR Tax
🛰️Switch from Meta: Muse Wonder to ScaleDown: Summarize
Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, Verified P90 latency of 280ms.