OpenAI: o3 (batch) vs Relace: Relace Search: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: o3 (batch) (openai/o3:batch) vs Relace: Relace Search (relace/relace-search). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: o3 (batch) (openai/o3:batch) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 75% automatic prefix caching ($0.50/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
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 OpenAI: o3 (batch) (API ID: openai/o3:batch) vs Relace: Relace Search (API ID: relace/relace-search), OpenAI: o3 (batch) offers lower standard input pricing at $1/1M tokens ($4/1M output), while OpenAI: o3 (batch) leads in cached prefix economics at $0.5/1M tokens (50% discount). OpenAI: o3 (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 | OpenAI: o3 (batch) | Relace: Relace Search | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/o3:batch | relace/relace-search | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $4 | $1 / $3 | OpenAI: o3 (batch) |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.5/1M (50% Off) | OpenAI: o3 (batch) |
| Context Window / Max Output | 195K In / 98K Out | 250K In / 125K Out | Relace: Relace Search |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: o3 (batch) (-0ms) |
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instru
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 OpenAI: o3 (batch) 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.