Relace: Relace Search vs Qwen: Qwen3.5-27B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Relace: Relace Search (relace/relace-search) vs Qwen: Qwen3.5-27B (qwen/qwen3.5-27b). 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.
Qwen: Qwen3.5-27B (qwen/qwen3.5-27b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5-27B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.13/1M) 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 Qwen: Qwen3.5-27B (API ID: qwen/qwen3.5-27b), Qwen: Qwen3.5-27B offers lower standard input pricing at $0.26/1M tokens ($2.6/1M output), while Qwen: Qwen3.5-27B leads in cached prefix economics at $0.13/1M 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 | Qwen: Qwen3.5-27B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | relace/relace-search | qwen/qwen3.5-27b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $3 | $0.26 / $2.6 | Qwen: Qwen3.5-27B |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.13/1M (50% Off) | Qwen: Qwen3.5-27B |
| Context Window / Max Output | 250K In / 125K Out | 256K In / 80K 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
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its ov
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 Qwen: Qwen3.5-27B
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its ov Verified P90 latency of 280ms.