Inception: Mercury 3 vs Z.ai: GLM 5.2: Live Promos, Pricing, Hidden Fees & Latency
Inception: Mercury 3 (inception/mercury-3) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Inception: Mercury 3: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM 5.2 (z-ai/glm-5.2) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 5.2: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.31/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Inception: Mercury 3 (API ID: inception/mercury-3) vs Z.ai: GLM 5.2 (API ID: z-ai/glm-5.2), Inception: Mercury 3 offers lower standard input pricing at $0.1/1M tokens ($0.35/1M output), while Inception: Mercury 3 leads in cached prefix economics at $0.05/1M tokens (50% discount). Inception: Mercury 3 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 | Inception: Mercury 3 | Z.ai: GLM 5.2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | inception/mercury-3 | z-ai/glm-5.2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.35 | $0.62 / $2.42 | Inception: Mercury 3 |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $0.31/1M (50% Off) | Inception: Mercury 3 |
| Context Window / Max Output | 977K In / 128K Out | 1024K In / 922K Out | Z.ai: GLM 5.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Inception: Mercury 3 (-0ms) |
Mercury 3 is a diffusion-based language model from Inception, and the lab's most capable model to date. It is suited for agentic workflows and real-time applications where latency
GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level
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 Inception: Mercury 3 to Z.ai: GLM 5.2
GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level Verified P90 latency of 280ms.