Qwen: Qwen3.8 2.4T A95B vs Sakana: Fugu Ultra v2: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b) vs Sakana: Fugu Ultra v2 (sakana/fugu-ultra-v2). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.8 2.4T A95B: 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.
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: Qwen3.8 2.4T A95B (API ID: qwen/qwen3.8-2.4t-a95b) vs Sakana: Fugu Ultra v2 (API ID: sakana/fugu-ultra-v2), Qwen: Qwen3.8 2.4T A95B offers lower standard input pricing at $2/1M tokens ($6/1M output), while Qwen: Qwen3.8 2.4T A95B leads in cached prefix economics at $1/1M tokens (50% discount). Qwen: Qwen3.8 2.4T A95B 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: Qwen3.8 2.4T A95B | Sakana: Fugu Ultra v2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.8-2.4t-a95b | sakana/fugu-ultra-v2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $6 | $5 / $30 | Qwen: Qwen3.8 2.4T A95B |
| Cache Read Price (per 1M) | $1/1M (50% Off) | $2.5/1M (50% Off) | Qwen: Qwen3.8 2.4T A95B |
| Context Window / Max Output | 1024K In / 128K Out | 977K In / 125K Out | Qwen: Qwen3.8 2.4T A95B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.8 2.4T A95B (-0ms) |
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out
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: Qwen3.8 2.4T A95B 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.