Z.ai: GLM 4.6V vs Inception: Mercury 2.5: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Z.ai: GLM 4.6V (z-ai/glm-4.6v) vs Inception: Mercury 2.5 (inception/mercury-2.5). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Z.ai: GLM 4.6V (z-ai/glm-4.6v) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.6V: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.15/1M) or route via asynchronous Batch API for 50% off standard token rates.
Inception: Mercury 2.5 (inception/mercury-2.5) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Inception: Mercury 2.5: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.02/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Z.ai: GLM 4.6V (API ID: z-ai/glm-4.6v) vs Inception: Mercury 2.5 (API ID: inception/mercury-2.5), Inception: Mercury 2.5 offers lower standard input pricing at $0.04/1M tokens ($0.15/1M output), while Inception: Mercury 2.5 leads in cached prefix economics at $0.02/1M tokens (50% discount). Z.ai: GLM 4.6V 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 4.6V | Inception: Mercury 2.5 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | z-ai/glm-4.6v | inception/mercury-2.5 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.3 / $0.9 | $0.04 / $0.15 | Inception: Mercury 2.5 |
| Cache Read Price (per 1M) | $0.15/1M (50% Off) | $0.02/1M (50% Off) | Inception: Mercury 2.5 |
| Context Window / Max Output | 128K In / 32K Out | 254K In / 64K Out | Inception: Mercury 2.5 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Z.ai: GLM 4.6V (-0ms) |
GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K to
Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception. Instead of generating tokens sequentially, Mercury 2.5 produces and refines multiple t
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 4.6V to Inception: Mercury 2.5
Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception. Instead of generating tokens sequentially, Mercury 2.5 produces and refines multiple t Verified P90 latency of 280ms.