DeepSeek-R1 (Reasoner) vs DeepSeek: DeepSeek V4.1 Flash: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek-R1 (Reasoner) (deepseek-reasoner) vs DeepSeek: DeepSeek V4.1 Flash (deepseek/deepseek-v4.1-flash). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek-R1 (Reasoner) (deepseek-reasoner) — Automatic Disk KV Cache ($0.275/1M) & 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.
DeepSeek: DeepSeek V4.1 Flash (deepseek/deepseek-v4.1-flash) — Automatic Disk KV Cache ($0.0069/1M) & 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.
In Etuki October 2026 FinOps telemetry comparing DeepSeek-R1 (Reasoner) (API ID: deepseek-reasoner) vs DeepSeek: DeepSeek V4.1 Flash (API ID: deepseek/deepseek-v4.1-flash), DeepSeek: DeepSeek V4.1 Flash offers lower standard input pricing at $0.0137/1M tokens ($0.891/1M output), while DeepSeek: DeepSeek V4.1 Flash leads in cached prefix economics at $0.0069/1M tokens (50% discount). DeepSeek: DeepSeek V4.1 Flash achieves a 260ms faster P90 time-to-first-token latency (280ms vs 540ms).
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | DeepSeek-R1 (Reasoner) | DeepSeek: DeepSeek V4.1 Flash | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek-reasoner | deepseek/deepseek-v4.1-flash | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.55 / $2.19 | $0.0137 / $0.891 | DeepSeek: DeepSeek V4.1 Flash |
| Cache Read Price (per 1M) | $0.275/1M (50% Off) | $0.0069/1M (50% Off) | DeepSeek: DeepSeek V4.1 Flash |
| Context Window / Max Output | 400K In / 128K Out | 1024K In / 922K Out | DeepSeek: DeepSeek V4.1 Flash |
| P90 First-Token / Edge Latency | 540ms | 280ms | DeepSeek: DeepSeek V4.1 Flash (-260ms) |
Open-weight reinforcement-learning reasoning model for formal math, finance, and theorem synthesis.
DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters o
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-R1 (Reasoner) to DeepSeek: DeepSeek V4.1 Flash
DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters o Verified P90 latency of 280ms.