Sakana: Sakana Namazu vs Mistral: Mistral Medium 3.5 (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Sakana: Sakana Namazu (sakana/sakana-namazu) vs Mistral: Mistral Medium 3.5 (batch) (mistralai/mistral-medium-3-5:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Mistral: Mistral Medium 3.5 (batch) (mistralai/mistral-medium-3-5:batch) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Mistral Medium 3.5 (batch): Activate ephemeral prefix caching to slash input costs by 50% (down to $0.375/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Sakana: Sakana Namazu (API ID: sakana/sakana-namazu) vs Mistral: Mistral Medium 3.5 (batch) (API ID: mistralai/mistral-medium-3-5:batch), Mistral: Mistral Medium 3.5 (batch) offers lower standard input pricing at $0.75/1M tokens ($3.75/1M output), while Mistral: Mistral Medium 3.5 (batch) leads in cached prefix economics at $0.375/1M tokens (50% discount). Sakana: Sakana Namazu 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: Sakana Namazu | Mistral: Mistral Medium 3.5 (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | sakana/sakana-namazu | mistralai/mistral-medium-3-5:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.95 / $4 | $0.75 / $3.75 | Mistral: Mistral Medium 3.5 (batch) |
| Cache Read Price (per 1M) | $0.475/1M (50% Off) | $0.375/1M (50% Off) | Mistral: Mistral Medium 3.5 (batch) |
| Context Window / Max Output | 256K In / 64K Out | 256K In / 205K Out | Mistral: Mistral Medium 3.5 (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Sakana: Sakana Namazu (-0ms) |
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
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, a
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: Sakana Namazu to Mistral: Mistral Medium 3.5 (batch)
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, a Verified P90 latency of 280ms.