Tencent: Hunyuan A13B Instruct vs Meta: Llama Guard 4 12B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Tencent: Hunyuan A13B Instruct (tencent/hunyuan-a13b-instruct) vs Meta: Llama Guard 4 12B (meta-llama/llama-guard-4-12b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Meta: Llama Guard 4 12B (meta-llama/llama-guard-4-12b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama Guard 4 12B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.09/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Tencent: Hunyuan A13B Instruct (API ID: tencent/hunyuan-a13b-instruct) vs Meta: Llama Guard 4 12B (API ID: meta-llama/llama-guard-4-12b), 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). Tencent: Hunyuan A13B Instruct 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 | Tencent: Hunyuan A13B Instruct | Meta: Llama Guard 4 12B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | tencent/hunyuan-a13b-instruct | meta-llama/llama-guard-4-12b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.14 / $0.57 | $0.18 / $0.18 | Tencent: Hunyuan A13B Instruct |
| Cache Read Price (per 1M) | $0.07/1M (50% Off) | $0.09/1M (50% Off) | Tencent: Hunyuan A13B Instruct |
| Context Window / Max Output | 128K In / 115K Out | 160K In / 16K Out | Tencent: Hunyuan A13B Instruct |
| P90 First-Token / Edge Latency | 280ms | 280ms | Tencent: Hunyuan A13B Instruct (-0ms) |
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
Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content
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 Tencent: Hunyuan A13B Instruct to Meta: Llama Guard 4 12B
Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content Verified P90 latency of 280ms.