Sakana: Sakana Namazu vs Poolside: Laguna S 2.1: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Sakana: Sakana Namazu (sakana/sakana-namazu) vs Poolside: Laguna S 2.1 (poolside/laguna-s-2.1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Sakana: Sakana Namazu (sakana/sakana-namazu) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sakana: Sakana Namazu: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.475/1M) or route via asynchronous Batch API for 50% off standard token rates.
Poolside: Laguna S 2.1 (poolside/laguna-s-2.1) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Poolside: Laguna S 2.1: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.045/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Sakana: Sakana Namazu (API ID: sakana/sakana-namazu) vs Poolside: Laguna S 2.1 (API ID: poolside/laguna-s-2.1), Poolside: Laguna S 2.1 offers lower standard input pricing at $0.09/1M tokens ($0.18/1M output), while Poolside: Laguna S 2.1 leads in cached prefix economics at $0.045/1M tokens (50% discount). Sakana: Sakana Namazu 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 | Sakana: Sakana Namazu | Poolside: Laguna S 2.1 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | sakana/sakana-namazu | poolside/laguna-s-2.1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.95 / $4 | $0.09 / $0.18 | Poolside: Laguna S 2.1 |
| Cache Read Price (per 1M) | $0.475/1M (50% Off) | $0.045/1M (50% Off) | Poolside: Laguna S 2.1 |
| Context Window / Max Output | 256K In / 64K Out | 1024K In / 128K Out | Poolside: Laguna S 2.1 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Sakana: Sakana Namazu (-0ms) |
Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Ja
Laguna S 2.1 is the latest coding agent model from [Poolside](<https://poolside.ai/>). Laguna S 2.1 is a 118B total parameter model with 8B active parameters, scoring 70.2% on Term
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 Sakana: Sakana Namazu to Poolside: Laguna S 2.1
Laguna S 2.1 is the latest coding agent model from [Poolside](<https://poolside.ai/>). Laguna S 2.1 is a 118B total parameter model with 8B active parameters, scoring 70.2% on Term Verified P90 latency of 280ms.