Sakana: Fugu Max vs Qwen: Qwen3.6 27B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Sakana: Fugu Max (sakana/fugu-max) vs Qwen: Qwen3.6 27B (qwen/qwen3.6-27b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Sakana: Fugu Max (sakana/fugu-max) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sakana: Fugu Max: Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen: Qwen3.6 27B (qwen/qwen3.6-27b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.6 27B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.16/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Sakana: Fugu Max (API ID: sakana/fugu-max) vs Qwen: Qwen3.6 27B (API ID: qwen/qwen3.6-27b), Qwen: Qwen3.6 27B offers lower standard input pricing at $0.32/1M tokens ($3.2/1M output), while Qwen: Qwen3.6 27B leads in cached prefix economics at $0.16/1M tokens (50% discount). Sakana: Fugu Max 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: Fugu Max | Qwen: Qwen3.6 27B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | sakana/fugu-max | qwen/qwen3.6-27b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $6 | $0.32 / $3.2 | Qwen: Qwen3.6 27B |
| Cache Read Price (per 1M) | $1/1M (50% Off) | $0.16/1M (50% Off) | Qwen: Qwen3.6 27B |
| Context Window / Max Output | 977K In / 125K Out | 256K In / 80K Out | Sakana: Fugu Max |
| P90 First-Token / Edge Latency | 280ms | 280ms | Sakana: Fugu Max (-0ms) |
Fugu Max is the cost-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 train
Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image
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: Fugu Max to Qwen: Qwen3.6 27B
Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image Verified P90 latency of 280ms.