MiniMax: MiniMax M2.5 vs Meta: Muse Spark 1.2: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MiniMax: MiniMax M2.5 (minimax/minimax-m2.5) vs Meta: Muse Spark 1.2 (meta/muse-spark-1.2). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MiniMax: MiniMax M2.5 (minimax/minimax-m2.5) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MiniMax: MiniMax M2.5: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.135/1M) 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 MiniMax: MiniMax M2.5 (API ID: minimax/minimax-m2.5) vs Meta: Muse Spark 1.2 (API ID: meta/muse-spark-1.2), MiniMax: MiniMax M2.5 offers lower standard input pricing at $0.27/1M tokens ($0.95/1M output), while MiniMax: MiniMax M2.5 leads in cached prefix economics at $0.135/1M tokens (50% discount). MiniMax: MiniMax M2.5 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 | MiniMax: MiniMax M2.5 | Meta: Muse Spark 1.2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | minimax/minimax-m2.5 | meta/muse-spark-1.2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.27 / $0.95 | $1.25 / $4.25 | MiniMax: MiniMax M2.5 |
| Cache Read Price (per 1M) | $0.135/1M (50% Off) | $0.625/1M (50% Off) | MiniMax: MiniMax M2.5 |
| Context Window / Max Output | 200K In / 32K Out | 1024K In / 922K Out | Meta: Muse Spark 1.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | MiniMax: MiniMax M2.5 (-0ms) |
MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon th
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 MiniMax: MiniMax M2.5 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.