Mistral: Mistral Small 3.2 24B vs Z.ai: GLM 4.5V: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Mistral: Mistral Small 3.2 24B (mistralai/mistral-small-3.2-24b-instruct) vs Z.ai: GLM 4.5V (z-ai/glm-4.5v). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Mistral: Mistral Small 3.2 24B (mistralai/mistral-small-3.2-24b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Mistral: Mistral Small 3.2 24B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0469/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM 4.5V (z-ai/glm-4.5v) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.5V: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.3/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Mistral: Mistral Small 3.2 24B (API ID: mistralai/mistral-small-3.2-24b-instruct) vs Z.ai: GLM 4.5V (API ID: z-ai/glm-4.5v), Mistral: Mistral Small 3.2 24B offers lower standard input pricing at $0.0938/1M tokens ($0.25/1M output), while Mistral: Mistral Small 3.2 24B leads in cached prefix economics at $0.0469/1M tokens (50% discount). Mistral: Mistral Small 3.2 24B 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: Mistral Small 3.2 24B | Z.ai: GLM 4.5V | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | mistralai/mistral-small-3.2-24b-instruct | z-ai/glm-4.5v | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.0938 / $0.25 | $0.6 / $1.8 | Mistral: Mistral Small 3.2 24B |
| Cache Read Price (per 1M) | $0.0469/1M (50% Off) | $0.3/1M (50% Off) | Mistral: Mistral Small 3.2 24B |
| Context Window / Max Output | 250K In / 16K Out | 64K In / 16K Out | Mistral: Mistral Small 3.2 24B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Mistral: Mistral Small 3.2 24B (-0ms) |
Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compare
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters
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: Mistral Small 3.2 24B to Z.ai: GLM 4.5V
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters Verified P90 latency of 280ms.