Qwen: Qwen3 32B vs Sakana: Fugu Ultra v2: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3 32B (qwen/qwen3-32b) vs Sakana: Fugu Ultra v2 (sakana/fugu-ultra-v2). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3 32B (qwen/qwen3-32b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3 32B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.04/1M) or route via asynchronous Batch API for 50% off standard token rates.
Sakana: Fugu Ultra v2 (sakana/fugu-ultra-v2) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sakana: Fugu Ultra v2: 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 Qwen: Qwen3 32B (API ID: qwen/qwen3-32b) vs Sakana: Fugu Ultra v2 (API ID: sakana/fugu-ultra-v2), Qwen: Qwen3 32B offers lower standard input pricing at $0.08/1M tokens ($0.28/1M output), while Qwen: Qwen3 32B leads in cached prefix economics at $0.04/1M tokens (50% discount). Qwen: Qwen3 32B 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 | Qwen: Qwen3 32B | Sakana: Fugu Ultra v2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3-32b | sakana/fugu-ultra-v2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.08 / $0.28 | $5 / $30 | Qwen: Qwen3 32B |
| Cache Read Price (per 1M) | $0.04/1M (50% Off) | $2.5/1M (50% Off) | Qwen: Qwen3 32B |
| Context Window / Max Output | 128K In / 16K Out | 977K In / 125K Out | Sakana: Fugu Ultra v2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3 32B (-0ms) |
Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching betwee
Fugu Ultra v2 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 mode
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 Qwen: Qwen3 32B to Sakana: Fugu Ultra v2
Fugu Ultra v2 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 mode Verified P90 latency of 280ms.