Perceptron: Perceptron Mk1 vs Z.ai: GLM 4.6: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Perceptron: Perceptron Mk1 (perceptron/perceptron-mk1) vs Z.ai: GLM 4.6 (z-ai/glm-4.6). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Perceptron: Perceptron Mk1 (perceptron/perceptron-mk1) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Perceptron: Perceptron Mk1: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.075/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM 4.6 (z-ai/glm-4.6) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.6: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.25/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Perceptron: Perceptron Mk1 (API ID: perceptron/perceptron-mk1) vs Z.ai: GLM 4.6 (API ID: z-ai/glm-4.6), Perceptron: Perceptron Mk1 offers lower standard input pricing at $0.15/1M tokens ($1.5/1M output), while Perceptron: Perceptron Mk1 leads in cached prefix economics at $0.075/1M tokens (50% discount). Perceptron: Perceptron Mk1 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 | Perceptron: Perceptron Mk1 | Z.ai: GLM 4.6 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | perceptron/perceptron-mk1 | z-ai/glm-4.6 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.15 / $1.5 | $0.5 / $2 | Perceptron: Perceptron Mk1 |
| Cache Read Price (per 1M) | $0.075/1M (50% Off) | $0.25/1M (50% Off) | Perceptron: Perceptron Mk1 |
| Context Window / Max Output | 32K In / 8K Out | 200K In / 128K Out | Z.ai: GLM 4.6 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Perceptron: Perceptron Mk1 (-0ms) |
Perceptron Mk1 (Mark One) is Perceptron's highest-quality vision-language model for video and embodied reasoning.** It accepts image and video inputs paired with natural language q
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to
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 Perceptron: Perceptron Mk1 to Z.ai: GLM 4.6
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to Verified P90 latency of 280ms.