Sakana: Fugu Max vs Cohere: Command R (08-2024): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Sakana: Fugu Max (sakana/fugu-max) vs Cohere: Command R (08-2024) (cohere/command-r-08-2024). 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.
Cohere: Command R (08-2024) (cohere/command-r-08-2024) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Cohere: Command R (08-2024): Activate ephemeral prefix caching to slash input costs by 50% (down to $0.075/1M) 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 Cohere: Command R (08-2024) (API ID: cohere/command-r-08-2024), Cohere: Command R (08-2024) offers lower standard input pricing at $0.15/1M tokens ($0.6/1M output), while Cohere: Command R (08-2024) leads in cached prefix economics at $0.075/1M 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 | Cohere: Command R (08-2024) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | sakana/fugu-max | cohere/command-r-08-2024 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $6 | $0.15 / $0.6 | Cohere: Command R (08-2024) |
| Cache Read Price (per 1M) | $1/1M (50% Off) | $0.075/1M (50% Off) | Cohere: Command R (08-2024) |
| Context Window / Max Output | 977K In / 125K Out | 125K In / 4K 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
command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broad
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 Cohere: Command R (08-2024)
command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broad Verified P90 latency of 280ms.