NVIDIA: Nemotron 3.5 Content Safety vs Tencent: Hunyuan A13B Instruct: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing NVIDIA: Nemotron 3.5 Content Safety (nvidia/nemotron-3.5-content-safety) vs Tencent: Hunyuan A13B Instruct (tencent/hunyuan-a13b-instruct). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
NVIDIA: Nemotron 3.5 Content Safety (nvidia/nemotron-3.5-content-safety) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for NVIDIA: Nemotron 3.5 Content Safety: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.1/1M) or route via asynchronous Batch API for 50% off standard token rates.
Tencent: Hunyuan A13B Instruct (tencent/hunyuan-a13b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Tencent: Hunyuan A13B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.07/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing NVIDIA: Nemotron 3.5 Content Safety (API ID: nvidia/nemotron-3.5-content-safety) vs Tencent: Hunyuan A13B Instruct (API ID: tencent/hunyuan-a13b-instruct), Tencent: Hunyuan A13B Instruct offers lower standard input pricing at $0.14/1M tokens ($0.57/1M output), while Tencent: Hunyuan A13B Instruct leads in cached prefix economics at $0.07/1M tokens (50% discount). NVIDIA: Nemotron 3.5 Content Safety 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 | NVIDIA: Nemotron 3.5 Content Safety | Tencent: Hunyuan A13B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | nvidia/nemotron-3.5-content-safety | tencent/hunyuan-a13b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.2 / $0.2 | $0.14 / $0.57 | Tencent: Hunyuan A13B Instruct |
| Cache Read Price (per 1M) | $0.1/1M (50% Off) | $0.07/1M (50% Off) | Tencent: Hunyuan A13B Instruct |
| Context Window / Max Output | 128K In / 115K Out | 128K In / 115K Out | NVIDIA: Nemotron 3.5 Content Safety |
| P90 First-Token / Edge Latency | 280ms | 280ms | NVIDIA: Nemotron 3.5 Content Safety (-0ms) |
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
Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thou
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 NVIDIA: Nemotron 3.5 Content Safety to Tencent: Hunyuan A13B Instruct
Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thou Verified P90 latency of 280ms.