DeepSeek: DeepSeek V4 Pro 0423 vs DeepSeek: R1: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V4 Pro 0423 (deepseek/deepseek-v4-pro) vs DeepSeek: R1 (deepseek/deepseek-r1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek V4 Pro 0423 (deepseek/deepseek-v4-pro) — Automatic Disk KV Cache ($0.2112/1M) & 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: R1 (deepseek/deepseek-r1) — Automatic Disk KV Cache ($0.35/1M) & 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: DeepSeek V4 Pro 0423 (API ID: deepseek/deepseek-v4-pro) vs DeepSeek: R1 (API ID: deepseek/deepseek-r1), DeepSeek: DeepSeek V4 Pro 0423 offers lower standard input pricing at $0.4225/1M tokens ($0.8449/1M output), while DeepSeek: DeepSeek V4 Pro 0423 leads in cached prefix economics at $0.2112/1M 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 | DeepSeek: R1 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v4-pro | deepseek/deepseek-r1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.4225 / $0.8449 | $0.7 / $2.5 | DeepSeek: DeepSeek V4 Pro 0423 |
| Cache Read Price (per 1M) | $0.2112/1M (50% Off) | $0.35/1M (50% Off) | DeepSeek: DeepSeek V4 Pro 0423 |
| Context Window / Max Output | 1024K In / 375K Out | 63K 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
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inf
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 DeepSeek: R1
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inf Verified P90 latency of 280ms.