Z.ai: GLM 4.6V vs Mistral: Saba: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Z.ai: GLM 4.6V (z-ai/glm-4.6v) vs Mistral: Saba (mistralai/mistral-saba). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Z.ai: GLM 4.6V (z-ai/glm-4.6v) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.6V: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.15/1M) or route via asynchronous Batch API for 50% off standard token rates.
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.
In Etuki October 2026 FinOps telemetry comparing Z.ai: GLM 4.6V (API ID: z-ai/glm-4.6v) vs Mistral: Saba (API ID: mistralai/mistral-saba), 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). Z.ai: GLM 4.6V 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 | Z.ai: GLM 4.6V | Mistral: Saba | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | z-ai/glm-4.6v | mistralai/mistral-saba | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.3 / $0.9 | $0.2 / $0.6 | Mistral: Saba |
| Cache Read Price (per 1M) | $0.15/1M (50% Off) | $0.1/1M (50% Off) | Mistral: Saba |
| Context Window / Max Output | 128K In / 32K Out | 32K In / 26K Out | Z.ai: GLM 4.6V |
| P90 First-Token / Edge Latency | 280ms | 280ms | Z.ai: GLM 4.6V (-0ms) |
GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K to
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
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 Z.ai: GLM 4.6V to Mistral: Saba
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 Verified P90 latency of 280ms.