Fireworks: Ember-1 vs Relace: Relace Search: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Fireworks: Ember-1 (fireworks/ember-1) vs Relace: Relace Search (relace/relace-search). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Fireworks: Ember-1 (fireworks/ember-1) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Fireworks: Ember-1: Activate ephemeral prefix caching to slash input costs by 50% (down to $1.5/1M) 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 Fireworks: Ember-1 (API ID: fireworks/ember-1) vs Relace: Relace Search (API ID: relace/relace-search), 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). Fireworks: Ember-1 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 | Fireworks: Ember-1 | Relace: Relace Search | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | fireworks/ember-1 | relace/relace-search | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $3 / $15 | $1 / $3 | Relace: Relace Search |
| Cache Read Price (per 1M) | $1.5/1M (50% Off) | $0.5/1M (50% Off) | Relace: Relace Search |
| Context Window / Max Output | 1024K In / 922K Out | 250K In / 125K Out | Fireworks: Ember-1 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Fireworks: Ember-1 (-0ms) |
Ember-1 is a specialized reasoning model from Fireworks Research, built on [Kimi K3](https://openrouter.ai/moonshotai/kimi-k3). It is designed to make every token go further: it 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 Fireworks: Ember-1 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.