Z.ai: GLM 4.7 Flash vs Thinking Machines: Inkling: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Z.ai: GLM 4.7 Flash (z-ai/glm-4.7-flash) vs Thinking Machines: Inkling (thinkingmachines/inkling). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Z.ai: GLM 4.7 Flash (z-ai/glm-4.7-flash) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.7 Flash: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0302/1M) 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 Z.ai: GLM 4.7 Flash (API ID: z-ai/glm-4.7-flash) vs Thinking Machines: Inkling (API ID: thinkingmachines/inkling), Z.ai: GLM 4.7 Flash offers lower standard input pricing at $0.0605/1M tokens ($0.4/1M output), while Z.ai: GLM 4.7 Flash leads in cached prefix economics at $0.0302/1M tokens (50% discount). Z.ai: GLM 4.7 Flash 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 4.7 Flash | Thinking Machines: Inkling | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | z-ai/glm-4.7-flash | thinkingmachines/inkling | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.0605 / $0.4 | $1 / $4.05 | Z.ai: GLM 4.7 Flash |
| Cache Read Price (per 1M) | $0.0302/1M (50% Off) | $0.5/1M (50% Off) | Z.ai: GLM 4.7 Flash |
| Context Window / Max Output | 195K In / 115K Out | 512K In / 461K Out | Thinking Machines: Inkling |
| P90 First-Token / Edge Latency | 280ms | 280ms | Z.ai: GLM 4.7 Flash (-0ms) |
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding ca
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 Z.ai: GLM 4.7 Flash 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.