Sakana: Sakana Namazu vs Qwen: Qwen3.5 Plus 2026-02-15: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Sakana: Sakana Namazu (sakana/sakana-namazu) vs Qwen: Qwen3.5 Plus 2026-02-15 (qwen/qwen3.5-plus-02-15). 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.
Qwen: Qwen3.5 Plus 2026-02-15 (qwen/qwen3.5-plus-02-15) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5 Plus 2026-02-15: 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 Sakana: Sakana Namazu (API ID: sakana/sakana-namazu) vs Qwen: Qwen3.5 Plus 2026-02-15 (API ID: qwen/qwen3.5-plus-02-15), Qwen: Qwen3.5 Plus 2026-02-15 offers lower standard input pricing at $0.26/1M tokens ($1.56/1M output), while Qwen: Qwen3.5 Plus 2026-02-15 leads in cached prefix economics at $0.13/1M 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 | Qwen: Qwen3.5 Plus 2026-02-15 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | sakana/sakana-namazu | qwen/qwen3.5-plus-02-15 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.95 / $4 | $0.26 / $1.56 | Qwen: Qwen3.5 Plus 2026-02-15 |
| Cache Read Price (per 1M) | $0.475/1M (50% Off) | $0.13/1M (50% Off) | Qwen: Qwen3.5 Plus 2026-02-15 |
| Context Window / Max Output | 256K In / 64K Out | 977K In / 64K Out | Sakana: Sakana Namazu |
| 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
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achievin
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 Qwen: Qwen3.5 Plus 2026-02-15
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achievin Verified P90 latency of 280ms.