Meta: Llama 4 Scout vs Amazon: Nova Premier 1.0: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Llama 4 Scout (meta-llama/llama-4-scout) vs Amazon: Nova Premier 1.0 (amazon/nova-premier-v1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Llama 4 Scout (meta-llama/llama-4-scout) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 4 Scout: 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.
Amazon: Nova Premier 1.0 (amazon/nova-premier-v1) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Amazon: Nova Premier 1.0: Activate ephemeral prefix caching to slash input costs by 50% (down to $1.25/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Llama 4 Scout (API ID: meta-llama/llama-4-scout) vs Amazon: Nova Premier 1.0 (API ID: amazon/nova-premier-v1), Meta: Llama 4 Scout offers lower standard input pricing at $0.18/1M tokens ($0.59/1M output), while Meta: Llama 4 Scout leads in cached prefix economics at $0.09/1M tokens (50% discount). Meta: Llama 4 Scout 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 4 Scout | Amazon: Nova Premier 1.0 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-4-scout | amazon/nova-premier-v1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.18 / $0.59 | $2.5 / $12.5 | Meta: Llama 4 Scout |
| Cache Read Price (per 1M) | $0.09/1M (50% Off) | $1.25/1M (50% Off) | Meta: Llama 4 Scout |
| Context Window / Max Output | 1280K In / 115K Out | 977K In / 31K Out | Meta: Llama 4 Scout |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama 4 Scout (-0ms) |
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimo
Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models.
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 4 Scout to Amazon: Nova Premier 1.0
Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models. Verified P90 latency of 280ms.