DeepSeek: DeepSeek V3.2 Exp vs MoonshotAI: Kimi K2 Thinking: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp) vs MoonshotAI: Kimi K2 Thinking (moonshotai/kimi-k2-thinking). 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.
MoonshotAI: Kimi K2 Thinking (moonshotai/kimi-k2-thinking) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K2 Thinking: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.3/1M) 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 MoonshotAI: Kimi K2 Thinking (API ID: moonshotai/kimi-k2-thinking), 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 | MoonshotAI: Kimi K2 Thinking | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3.2-exp | moonshotai/kimi-k2-thinking | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.27 / $0.41 | $0.6 / $2.5 | DeepSeek: DeepSeek V3.2 Exp |
| Cache Read Price (per 1M) | $0.135/1M (50% Off) | $0.3/1M (50% Off) | DeepSeek: DeepSeek V3.2 Exp |
| Context Window / Max Output | 160K In / 144K Out | 256K In / 96K 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
Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-
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 MoonshotAI: Kimi K2 Thinking
Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture- Verified P90 latency of 280ms.