Mistral: Saba vs Thinking Machines: Inkling: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Mistral: Saba (mistralai/mistral-saba) vs Thinking Machines: Inkling (thinkingmachines/inkling). 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.
Thinking Machines: Inkling (thinkingmachines/inkling) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Thinking Machines: Inkling: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.5/1M) 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 Thinking Machines: Inkling (API ID: thinkingmachines/inkling), 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 | Thinking Machines: Inkling | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | mistralai/mistral-saba | thinkingmachines/inkling | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.2 / $0.6 | $1 / $4.05 | Mistral: Saba |
| Cache Read Price (per 1M) | $0.1/1M (50% Off) | $0.5/1M (50% Off) | Mistral: Saba |
| Context Window / Max Output | 32K In / 26K Out | 512K In / 461K Out | Thinking Machines: Inkling |
| 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
Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning
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 Thinking Machines: Inkling
Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning Verified P90 latency of 280ms.