inclusionAI: Ling 3.0 Flash vs Relace: Relace Search: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing inclusionAI: Ling 3.0 Flash (inclusionai/ling-3.0-flash) vs Relace: Relace Search (relace/relace-search). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
inclusionAI: Ling 3.0 Flash (inclusionai/ling-3.0-flash) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for inclusionAI: Ling 3.0 Flash: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0105/1M) or route via asynchronous Batch API for 50% off standard token rates.
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.
In Etuki October 2026 FinOps telemetry comparing inclusionAI: Ling 3.0 Flash (API ID: inclusionai/ling-3.0-flash) vs Relace: Relace Search (API ID: relace/relace-search), inclusionAI: Ling 3.0 Flash offers lower standard input pricing at $0.021/1M tokens ($0.063/1M output), while inclusionAI: Ling 3.0 Flash leads in cached prefix economics at $0.0105/1M tokens (50% discount). inclusionAI: Ling 3.0 Flash 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 | inclusionAI: Ling 3.0 Flash | Relace: Relace Search | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | inclusionai/ling-3.0-flash | relace/relace-search | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.021 / $0.063 | $1 / $3 | inclusionAI: Ling 3.0 Flash |
| Cache Read Price (per 1M) | $0.0105/1M (50% Off) | $0.5/1M (50% Off) | inclusionAI: Ling 3.0 Flash |
| Context Window / Max Output | 256K In / 32K Out | 250K In / 125K Out | Relace: Relace Search |
| P90 First-Token / Edge Latency | 280ms | 280ms | inclusionAI: Ling 3.0 Flash (-0ms) |
*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and pr
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
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 inclusionAI: Ling 3.0 Flash to Relace: Relace Search
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 Verified P90 latency of 280ms.