Inference.net: Schematron V2 Turbo vs Sakana: Fugu Ultra: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Inference.net: Schematron V2 Turbo (inference-net/schematron-v2-turbo) vs Sakana: Fugu Ultra (sakana/fugu-ultra). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Inference.net: Schematron V2 Turbo (inference-net/schematron-v2-turbo) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Inference.net: Schematron V2 Turbo: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.015/1M) or route via asynchronous Batch API for 50% off standard token rates.
Sakana: Fugu Ultra (sakana/fugu-ultra) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sakana: Fugu Ultra: Activate ephemeral prefix caching to slash input costs by 50% (down to $2.5/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Inference.net: Schematron V2 Turbo (API ID: inference-net/schematron-v2-turbo) vs Sakana: Fugu Ultra (API ID: sakana/fugu-ultra), Inference.net: Schematron V2 Turbo offers lower standard input pricing at $0.03/1M tokens ($0.15/1M output), while Inference.net: Schematron V2 Turbo leads in cached prefix economics at $0.015/1M tokens (50% discount). Inference.net: Schematron V2 Turbo 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 | Inference.net: Schematron V2 Turbo | Sakana: Fugu Ultra | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | inference-net/schematron-v2-turbo | sakana/fugu-ultra | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.03 / $0.15 | $5 / $30 | Inference.net: Schematron V2 Turbo |
| Cache Read Price (per 1M) | $0.015/1M (50% Off) | $2.5/1M (50% Off) | Inference.net: Schematron V2 Turbo |
| Context Window / Max Output | 125K In / 8K Out | 977K In / 125K Out | Sakana: Fugu Ultra |
| P90 First-Token / Edge Latency | 280ms | 280ms | Inference.net: Schematron V2 Turbo (-0ms) |
Schematron V2 Turbo is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes throughput for high-volume extraction workloads. Extraction instructions must
Fugu Ultra is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model t
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 Inference.net: Schematron V2 Turbo to Sakana: Fugu Ultra
Fugu Ultra is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model t Verified P90 latency of 280ms.