DeepSeek: DeepSeek V4 Pro 0423 vs Meta: Llama Guard 4 12B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V4 Pro 0423 (deepseek/deepseek-v4-pro) vs Meta: Llama Guard 4 12B (meta-llama/llama-guard-4-12b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek V4 Pro 0423 (deepseek/deepseek-v4-pro) — Automatic Disk KV Cache ($0.4777/1M) & Off-Peak Promo
DeepSeek-V4 Pro (1.6T MoE) automatically caches repeated 64-token prompt prefixes on NVMe storage at $0.07/1M input tokens (50% off $0.14 base) with zero code changes required, plus off-peak UTC scheduling discounts.
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 DeepSeek: DeepSeek V4 Pro 0423 (API ID: deepseek/deepseek-v4-pro) vs Meta: Llama Guard 4 12B (API ID: meta-llama/llama-guard-4-12b), Meta: Llama Guard 4 12B offers lower standard input pricing at $0.18/1M tokens ($0.18/1M output), while Meta: Llama Guard 4 12B leads in cached prefix economics at $0.09/1M tokens (50% discount). DeepSeek: DeepSeek V4 Pro 0423 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 | DeepSeek: DeepSeek V4 Pro 0423 | Meta: Llama Guard 4 12B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v4-pro | meta-llama/llama-guard-4-12b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.9553 / $1.9105 | $0.18 / $0.18 | Meta: Llama Guard 4 12B |
| Cache Read Price (per 1M) | $0.4777/1M (50% Off) | $0.09/1M (50% Off) | Meta: Llama Guard 4 12B |
| Context Window / Max Output | 1024K In / 375K Out | 160K In / 16K Out | DeepSeek: DeepSeek V4 Pro 0423 |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: DeepSeek V4 Pro 0423 (-0ms) |
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designe
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 DeepSeek: DeepSeek V4 Pro 0423 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.