Meta: Llama Guard 4 12B vs Qwen: Qwen3.5-9B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Llama Guard 4 12B (meta-llama/llama-guard-4-12b) vs Qwen: Qwen3.5-9B (qwen/qwen3.5-9b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Qwen: Qwen3.5-9B (qwen/qwen3.5-9b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5-9B: 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.
In Etuki October 2026 FinOps telemetry comparing Meta: Llama Guard 4 12B (API ID: meta-llama/llama-guard-4-12b) vs Qwen: Qwen3.5-9B (API ID: qwen/qwen3.5-9b), Qwen: Qwen3.5-9B offers lower standard input pricing at $0.1/1M tokens ($0.15/1M output), while Qwen: Qwen3.5-9B leads in cached prefix economics at $0.05/1M tokens (50% discount). Meta: Llama Guard 4 12B 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 | Meta: Llama Guard 4 12B | Qwen: Qwen3.5-9B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-guard-4-12b | qwen/qwen3.5-9b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.18 / $0.18 | $0.1 / $0.15 | Qwen: Qwen3.5-9B |
| Cache Read Price (per 1M) | $0.09/1M (50% Off) | $0.05/1M (50% Off) | Qwen: Qwen3.5-9B |
| Context Window / Max Output | 160K In / 16K Out | 256K In / 32K Out | Qwen: Qwen3.5-9B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama Guard 4 12B (-0ms) |
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
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architectur
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 Meta: Llama Guard 4 12B to Qwen: Qwen3.5-9B
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architectur Verified P90 latency of 280ms.