OpenAI: GPT-6 Luna vs DeepSeek-V4 Pro: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: GPT-6 Luna (openai/gpt-6-luna) vs DeepSeek-V4 Pro (deepseek-v4-pro). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: GPT-6 Luna (openai/gpt-6-luna) 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).
Zero-Config Disk KV Cache ($0.07/1M) & Off-Peak UTC Batch Arbitrage
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 OpenAI: GPT-6 Luna (API ID: openai/gpt-6-luna) vs DeepSeek-V4 Pro (API ID: deepseek-v4-pro), OpenAI: GPT-6 Luna offers lower standard input pricing at $0.1/1M tokens ($0.5/1M output), while OpenAI: GPT-6 Luna leads in cached prefix economics at $0.05/1M tokens (50% discount). OpenAI: GPT-6 Luna achieves a 180ms faster P90 time-to-first-token latency (280ms vs 460ms).
Auto-discovered via live global telemetry registry.
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
| Specification / FinOps Dimension | OpenAI: GPT-6 Luna | DeepSeek-V4 Pro | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/gpt-6-luna | deepseek-v4-pro | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.5 | $0.14 / $0.28 | OpenAI: GPT-6 Luna |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $0.07/1M (50% Off) | OpenAI: GPT-6 Luna |
| Context Window / Max Output | 1025K In / 125K Out | 1000K In / 128K Out | DeepSeek-V4 Pro |
| P90 First-Token / Edge Latency | 280ms | 460ms | OpenAI: GPT-6 Luna (-180ms) |
GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classi
1.6-Trillion parameter (49B active) MoE architecture with Fine-Grained Sparse Attention and $0.07/1M disk KV cache hits.
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 OpenAI: GPT-6 Luna to DeepSeek-V4 Pro
1.6-Trillion parameter (49B active) MoE architecture with Fine-Grained Sparse Attention and $0.07/1M disk KV cache hits. Verified P90 latency of 460ms.