DeepSeek: DeepSeek V3.2 Exp vs OpenAI: o3 Mini (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp) vs OpenAI: o3 Mini (batch) (openai/o3-mini:batch). 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.
OpenAI: o3 Mini (batch) (openai/o3-mini:batch) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 75% automatic prefix caching ($0.50/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
In Etuki October 2026 FinOps telemetry comparing DeepSeek: DeepSeek V3.2 Exp (API ID: deepseek/deepseek-v3.2-exp) vs OpenAI: o3 Mini (batch) (API ID: openai/o3-mini:batch), 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 | OpenAI: o3 Mini (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3.2-exp | openai/o3-mini:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.27 / $0.41 | $0.55 / $2.2 | DeepSeek: DeepSeek V3.2 Exp |
| Cache Read Price (per 1M) | $0.135/1M (50% Off) | $0.275/1M (50% Off) | DeepSeek: DeepSeek V3.2 Exp |
| Context Window / Max Output | 160K In / 144K Out | 195K In / 98K 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
OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning
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 OpenAI: o3 Mini (batch)
OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning Verified P90 latency of 280ms.