Meta: Muse Spark 1.2 vs Reka Edge: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Muse Spark 1.2 (meta/muse-spark-1.2) vs Reka Edge (rekaai/reka-edge). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Reka Edge (rekaai/reka-edge) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Reka Edge: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Muse Spark 1.2 (API ID: meta/muse-spark-1.2) vs Reka Edge (API ID: rekaai/reka-edge), Reka Edge offers lower standard input pricing at $0.1/1M tokens ($0.1/1M output), while Reka Edge leads in cached prefix economics at $0.05/1M tokens (50% discount). Meta: Muse Spark 1.2 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 Spark 1.2 | Reka Edge | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta/muse-spark-1.2 | rekaai/reka-edge | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1.25 / $4.25 | $0.1 / $0.1 | Reka Edge |
| Cache Read Price (per 1M) | $0.625/1M (50% Off) | $0.05/1M (50% Off) | Reka Edge |
| Context Window / Max Output | 1024K In / 922K Out | 16K In / 14K Out | Meta: Muse Spark 1.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Muse Spark 1.2 (-0ms) |
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
Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to del
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 Spark 1.2 to Reka Edge
Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to del Verified P90 latency of 280ms.