Z.ai: GLM 4.6V vs NVIDIA: Nemotron 3.5 Content Safety (free): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Z.ai: GLM 4.6V (z-ai/glm-4.6v) vs NVIDIA: Nemotron 3.5 Content Safety (free) (nvidia/nemotron-3.5-content-safety:free). 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.
NVIDIA: Nemotron 3.5 Content Safety (free) (nvidia/nemotron-3.5-content-safety:free) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for NVIDIA: Nemotron 3.5 Content Safety (free): Activate ephemeral prefix caching to slash input costs by 50% (down to $0/1M) 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 NVIDIA: Nemotron 3.5 Content Safety (free) (API ID: nvidia/nemotron-3.5-content-safety:free), NVIDIA: Nemotron 3.5 Content Safety (free) offers lower standard input pricing at $0/1M tokens ($0/1M output), while NVIDIA: Nemotron 3.5 Content Safety (free) leads in cached prefix economics at $0/1M 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 | NVIDIA: Nemotron 3.5 Content Safety (free) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | z-ai/glm-4.6v | nvidia/nemotron-3.5-content-safety:free | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.3 / $0.9 | $0 / $0 | NVIDIA: Nemotron 3.5 Content Safety (free) |
| Cache Read Price (per 1M) | $0.15/1M (50% Off) | $0/1M (50% Off) | NVIDIA: Nemotron 3.5 Content Safety (free) |
| Context Window / Max Output | 128K In / 32K Out | 125K In / 8K Out | Z.ai: GLM 4.6V |
| 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
NVIDIA: Nemotron 3.5 Content Safety (free)
API ID: nvidia/nemotron-3.5-content-safety:free • Live RegistryNVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses fr
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 NVIDIA: Nemotron 3.5 Content Safety (free)
NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses fr Verified P90 latency of 280ms.