Mistral: Saba vs Sakana: Sakana Namazu: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Mistral: Saba (mistralai/mistral-saba) vs Sakana: Sakana Namazu (sakana/sakana-namazu). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Mistral: Saba (mistralai/mistral-saba) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Saba: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.1/1M) or route via asynchronous Batch API for 50% off standard token rates.
Sakana: Sakana Namazu (sakana/sakana-namazu) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sakana: Sakana Namazu: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.475/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Mistral: Saba (API ID: mistralai/mistral-saba) vs Sakana: Sakana Namazu (API ID: sakana/sakana-namazu), Mistral: Saba offers lower standard input pricing at $0.2/1M tokens ($0.6/1M output), while Mistral: Saba leads in cached prefix economics at $0.1/1M tokens (50% discount). Mistral: Saba 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 | Mistral: Saba | Sakana: Sakana Namazu | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | mistralai/mistral-saba | sakana/sakana-namazu | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.2 / $0.6 | $0.95 / $4 | Mistral: Saba |
| Cache Read Price (per 1M) | $0.1/1M (50% Off) | $0.475/1M (50% Off) | Mistral: Saba |
| Context Window / Max Output | 32K In / 26K Out | 256K In / 64K Out | Sakana: Sakana Namazu |
| P90 First-Token / Edge Latency | 280ms | 280ms | Mistral: Saba (-0ms) |
Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining e
Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Ja
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 Mistral: Saba to Sakana: Sakana Namazu
Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Ja Verified P90 latency of 280ms.