MoonshotAI: Kimi K3 (batch) vs Meta: Muse Spark Open: Live Promos, Pricing, Hidden Fees & Latency
MoonshotAI: Kimi K3 (batch) (moonshotai/kimi-k3:batch) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K3 (batch): Activate ephemeral prefix caching to slash input costs by 50% (down to 1.14/1M) or route via asynchronous Batch API for 50% off standard token rates.
Meta: Muse Spark Open (meta/muse-spark-open) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Muse Spark Open: 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 MoonshotAI: Kimi K3 (batch) (API ID: moonshotai/kimi-k3:batch) vs Meta: Muse Spark Open (API ID: meta/muse-spark-open), Meta: Muse Spark Open offers lower standard input pricing at $1.25/1M tokens ($4.25/1M output), while Meta: Muse Spark Open leads in cached prefix economics at $0.625/1M tokens (50% discount). MoonshotAI: Kimi K3 (batch) 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 | MoonshotAI: Kimi K3 (batch) | Meta: Muse Spark Open | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | moonshotai/kimi-k3:batch | meta/muse-spark-open | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2.28 / $11.4 | $1.25 / $4.25 | Meta: Muse Spark Open |
| Cache Read Price (per 1M) | $1.14/1M (50% Off) | $0.625/1M (50% Off) | Meta: Muse Spark Open |
| Context Window / Max Output | 1024K In / 16K Out | 1024K In / 922K Out | Meta: Muse Spark Open |
| P90 First-Token / Edge Latency | 280ms | 280ms | MoonshotAI: Kimi K3 (batch) (-0ms) |
Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is par
Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and de
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 MoonshotAI: Kimi K3 (batch) to Meta: Muse Spark Open
Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and de Verified P90 latency of 280ms.