ScaleDown: Summarize vs Meta: Muse Spark 1.2: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing ScaleDown: Summarize (scaledown/summarize) vs Meta: Muse Spark 1.2 (meta/muse-spark-1.2). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Meta: Muse Spark 1.2 (meta/muse-spark-1.2) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Muse Spark 1.2: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.625/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing ScaleDown: Summarize (API ID: scaledown/summarize) vs Meta: Muse Spark 1.2 (API ID: meta/muse-spark-1.2), 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). ScaleDown: Summarize 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 | ScaleDown: Summarize | Meta: Muse Spark 1.2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | scaledown/summarize | meta/muse-spark-1.2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.04 / $0 | $1.25 / $4.25 | ScaleDown: Summarize |
| Cache Read Price (per 1M) | $0.02/1M (50% Off) | $0.625/1M (50% Off) | ScaleDown: Summarize |
| Context Window / Max Output | 977K In / 4K Out | 1024K In / 922K Out | Meta: Muse Spark 1.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | ScaleDown: Summarize (-0ms) |
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,
Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, and PDF documents, returns text, and offers a 1M-token context wi
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 ScaleDown: Summarize to Meta: Muse Spark 1.2
Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, and PDF documents, returns text, and offers a 1M-token context wi Verified P90 latency of 280ms.