Relace: Relace Search vs MoonshotAI: Kimi K3 (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Relace: Relace Search (relace/relace-search) vs MoonshotAI: Kimi K3 (batch) (moonshotai/kimi-k3:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Relace: Relace Search (relace/relace-search) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Relace: Relace Search: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.5/1M) or route via asynchronous Batch API for 50% off standard token rates.
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.
In Etuki October 2026 FinOps telemetry comparing Relace: Relace Search (API ID: relace/relace-search) vs MoonshotAI: Kimi K3 (batch) (API ID: moonshotai/kimi-k3:batch), Relace: Relace Search offers lower standard input pricing at $1/1M tokens ($3/1M output), while Relace: Relace Search leads in cached prefix economics at $0.5/1M tokens (50% discount). Relace: Relace Search 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 | Relace: Relace Search | MoonshotAI: Kimi K3 (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | relace/relace-search | moonshotai/kimi-k3:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $3 | $2.28 / $11.4 | Relace: Relace Search |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $1.14/1M (50% Off) | Relace: Relace Search |
| Context Window / Max Output | 250K In / 125K Out | 1024K In / 16K Out | Relace: Relace Search |
| P90 First-Token / Edge Latency | 280ms | 280ms | Relace: Relace Search (-0ms) |
The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request. In contrast to RAG, relace-search pe
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
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 Relace: Relace Search to MoonshotAI: Kimi K3 (batch)
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 Verified P90 latency of 280ms.