DeepSeek: DeepSeek V3.2 Exp vs Amazon: Nova Premier 1.0: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp) vs Amazon: Nova Premier 1.0 (amazon/nova-premier-v1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp) — Automatic Disk KV Cache ($0.135/1M) & 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.
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 DeepSeek: DeepSeek V3.2 Exp (API ID: deepseek/deepseek-v3.2-exp) vs Amazon: Nova Premier 1.0 (API ID: amazon/nova-premier-v1), DeepSeek: DeepSeek V3.2 Exp offers lower standard input pricing at $0.27/1M tokens ($0.41/1M output), while DeepSeek: DeepSeek V3.2 Exp leads in cached prefix economics at $0.135/1M tokens (50% discount). DeepSeek: DeepSeek V3.2 Exp 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 V3.2 Exp | Amazon: Nova Premier 1.0 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3.2-exp | amazon/nova-premier-v1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.27 / $0.41 | $2.5 / $12.5 | DeepSeek: DeepSeek V3.2 Exp |
| Cache Read Price (per 1M) | $0.135/1M (50% Off) | $1.25/1M (50% Off) | DeepSeek: DeepSeek V3.2 Exp |
| Context Window / Max Output | 160K In / 144K Out | 977K In / 31K Out | DeepSeek: DeepSeek V3.2 Exp |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: DeepSeek V3.2 Exp (-0ms) |
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attentio
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 DeepSeek: DeepSeek V3.2 Exp 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.