Z.ai: GLM 4.5V vs Thinking Machines: Inkling Small: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Z.ai: GLM 4.5V (z-ai/glm-4.5v) vs Thinking Machines: Inkling Small (thinkingmachines/inkling-small). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Thinking Machines: Inkling Small (thinkingmachines/inkling-small) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Thinking Machines: Inkling Small: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.225/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Z.ai: GLM 4.5V (API ID: z-ai/glm-4.5v) vs Thinking Machines: Inkling Small (API ID: thinkingmachines/inkling-small), Thinking Machines: Inkling Small offers lower standard input pricing at $0.45/1M tokens ($1.2/1M output), while Thinking Machines: Inkling Small leads in cached prefix economics at $0.225/1M tokens (50% discount). Z.ai: GLM 4.5V 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 4.5V | Thinking Machines: Inkling Small | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | z-ai/glm-4.5v | thinkingmachines/inkling-small | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.6 / $1.8 | $0.45 / $1.2 | Thinking Machines: Inkling Small |
| Cache Read Price (per 1M) | $0.3/1M (50% Off) | $0.225/1M (50% Off) | Thinking Machines: Inkling Small |
| Context Window / Max Output | 64K In / 16K Out | 512K In / 256K Out | Thinking Machines: Inkling Small |
| P90 First-Token / Edge Latency | 280ms | 280ms | Z.ai: GLM 4.5V (-0ms) |
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
Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more
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 4.5V to Thinking Machines: Inkling Small
Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more Verified P90 latency of 280ms.