Meta: Muse Wonder vs Sakana: Fugu Max: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Muse Wonder (meta/muse-wonder) vs Sakana: Fugu Max (sakana/fugu-max). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Muse Wonder (meta/muse-wonder) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Muse Wonder: Activate ephemeral prefix caching to slash input costs by 50% (down to $2/1M) or route via asynchronous Batch API for 50% off standard token rates.
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.
In Etuki October 2026 FinOps telemetry comparing Meta: Muse Wonder (API ID: meta/muse-wonder) vs Sakana: Fugu Max (API ID: sakana/fugu-max), Sakana: Fugu Max offers lower standard input pricing at $2/1M tokens ($6/1M output), while Sakana: Fugu Max leads in cached prefix economics at $1/1M tokens (50% discount). Meta: Muse Wonder 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 | Meta: Muse Wonder | Sakana: Fugu Max | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta/muse-wonder | sakana/fugu-max | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $4 / $20 | $2 / $6 | Sakana: Fugu Max |
| Cache Read Price (per 1M) | $2/1M (50% Off) | $1/1M (50% Off) | Sakana: Fugu Max |
| Context Window / Max Output | 1024K In / 922K Out | 977K In / 125K Out | Meta: Muse Wonder |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Muse Wonder (-0ms) |
Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and retu
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
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 Meta: Muse Wonder to Sakana: Fugu Max
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 Verified P90 latency of 280ms.