Meta: Muse Spark 1.3 Contributor vs Sakana: Fugu Ultra v2: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Muse Spark 1.3 Contributor (meta/muse-spark-1.3-contributor) vs Sakana: Fugu Ultra v2 (sakana/fugu-ultra-v2). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Muse Spark 1.3 Contributor (meta/muse-spark-1.3-contributor) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Muse Spark 1.3 Contributor: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.05/1M) 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 Meta: Muse Spark 1.3 Contributor (API ID: meta/muse-spark-1.3-contributor) vs Sakana: Fugu Ultra v2 (API ID: sakana/fugu-ultra-v2), Meta: Muse Spark 1.3 Contributor offers lower standard input pricing at $0.1/1M tokens ($0.2/1M output), while Meta: Muse Spark 1.3 Contributor leads in cached prefix economics at $0.05/1M tokens (50% discount). Meta: Muse Spark 1.3 Contributor 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 Spark 1.3 Contributor | Sakana: Fugu Ultra v2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta/muse-spark-1.3-contributor | sakana/fugu-ultra-v2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.2 | $5 / $30 | Meta: Muse Spark 1.3 Contributor |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $2.5/1M (50% Off) | Meta: Muse Spark 1.3 Contributor |
| Context Window / Max Output | 1024K In / 922K Out | 977K In / 125K Out | Meta: Muse Spark 1.3 Contributor |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Muse Spark 1.3 Contributor (-0ms) |
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and codi
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 Meta: Muse Spark 1.3 Contributor 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.