StepFun: Step 3.5 Flash vs ScaleDown: Extract: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing StepFun: Step 3.5 Flash (stepfun/step-3.5-flash) vs ScaleDown: Extract (scaledown/extract). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
StepFun: Step 3.5 Flash (stepfun/step-3.5-flash) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for StepFun: Step 3.5 Flash: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
ScaleDown: Extract (scaledown/extract) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for ScaleDown: Extract: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.02/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing StepFun: Step 3.5 Flash (API ID: stepfun/step-3.5-flash) vs ScaleDown: Extract (API ID: scaledown/extract), ScaleDown: Extract offers lower standard input pricing at $0.04/1M tokens ($0/1M output), while ScaleDown: Extract leads in cached prefix economics at $0.02/1M tokens (50% discount). StepFun: Step 3.5 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 | StepFun: Step 3.5 Flash | ScaleDown: Extract | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | stepfun/step-3.5-flash | scaledown/extract | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.3 | $0.04 / $0 | ScaleDown: Extract |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $0.02/1M (50% Off) | ScaleDown: Extract |
| Context Window / Max Output | 256K In / 64K Out | 977K In / 879K Out | ScaleDown: Extract |
| P90 First-Token / Edge Latency | 280ms | 280ms | StepFun: Step 3.5 Flash (-0ms) |
Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parame
Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through `prov
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 StepFun: Step 3.5 Flash to ScaleDown: Extract
Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through `prov Verified P90 latency of 280ms.