Cohere: Command R (08-2024) vs DeepSeek: DeepSeek V4 Pro 0423: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Cohere: Command R (08-2024) (cohere/command-r-08-2024) vs DeepSeek: DeepSeek V4 Pro 0423 (deepseek/deepseek-v4-pro). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Cohere: Command R (08-2024) (cohere/command-r-08-2024) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Cohere: Command R (08-2024): Activate ephemeral prefix caching to slash input costs by 50% (down to $0.075/1M) or route via asynchronous Batch API for 50% off standard token rates.
DeepSeek: DeepSeek V4 Pro 0423 (deepseek/deepseek-v4-pro) — Automatic Disk KV Cache ($0.2213/1M) & 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 Cohere: Command R (08-2024) (API ID: cohere/command-r-08-2024) vs DeepSeek: DeepSeek V4 Pro 0423 (API ID: deepseek/deepseek-v4-pro), Cohere: Command R (08-2024) offers lower standard input pricing at $0.15/1M tokens ($0.6/1M output), while Cohere: Command R (08-2024) leads in cached prefix economics at $0.075/1M tokens (50% discount). Cohere: Command R (08-2024) 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 | Cohere: Command R (08-2024) | DeepSeek: DeepSeek V4 Pro 0423 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | cohere/command-r-08-2024 | deepseek/deepseek-v4-pro | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.15 / $0.6 | $0.4427 / $0.8853 | Cohere: Command R (08-2024) |
| Cache Read Price (per 1M) | $0.075/1M (50% Off) | $0.2213/1M (50% Off) | Cohere: Command R (08-2024) |
| Context Window / Max Output | 125K In / 4K Out | 1024K In / 375K Out | DeepSeek: DeepSeek V4 Pro 0423 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Cohere: Command R (08-2024) (-0ms) |
command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broad
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
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 Cohere: Command R (08-2024) to DeepSeek: DeepSeek V4 Pro 0423
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 Verified P90 latency of 280ms.