DeepSeek: DeepSeek V3.2 vs OpenAI: GPT-5.4 Nano (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V3.2 (deepseek/deepseek-v3.2) vs OpenAI: GPT-5.4 Nano (batch) (openai/gpt-5.4-nano:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek V3.2 (deepseek/deepseek-v3.2) — Automatic Disk KV Cache ($0.1295/1M) & 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: GPT-5.4 Nano (batch) (openai/gpt-5.4-nano: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 (API ID: deepseek/deepseek-v3.2) vs OpenAI: GPT-5.4 Nano (batch) (API ID: openai/gpt-5.4-nano:batch), OpenAI: GPT-5.4 Nano (batch) offers lower standard input pricing at $0.1/1M tokens ($0.625/1M output), while OpenAI: GPT-5.4 Nano (batch) leads in cached prefix economics at $0.05/1M tokens (50% discount). DeepSeek: DeepSeek V3.2 achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
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| Specification / FinOps Dimension | DeepSeek: DeepSeek V3.2 | OpenAI: GPT-5.4 Nano (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3.2 | openai/gpt-5.4-nano:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.259 / $0.8 | $0.1 / $0.625 | OpenAI: GPT-5.4 Nano (batch) |
| Cache Read Price (per 1M) | $0.1295/1M (50% Off) | $0.05/1M (50% Off) | OpenAI: GPT-5.4 Nano (batch) |
| Context Window / Max Output | 160K In / 144K Out | 391K In / 125K Out | DeepSeek: DeepSeek V3.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: DeepSeek V3.2 (-0ms) |
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse At
GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is
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 to OpenAI: GPT-5.4 Nano (batch)
GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is Verified P90 latency of 280ms.