OpenAI: GPT Astra Latest vs DeepSeek: DeepSeek V3.2 Exp: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: GPT Astra Latest (~openai/gpt-astra-latest) vs DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: GPT Astra Latest (~openai/gpt-astra-latest) 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).
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.
In Etuki October 2026 FinOps telemetry comparing OpenAI: GPT Astra Latest (API ID: ~openai/gpt-astra-latest) vs DeepSeek: DeepSeek V3.2 Exp (API ID: deepseek/deepseek-v3.2-exp), 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). OpenAI: GPT Astra Latest 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 | OpenAI: GPT Astra Latest | DeepSeek: DeepSeek V3.2 Exp | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | ~openai/gpt-astra-latest | deepseek/deepseek-v3.2-exp | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $10 / $50 | $0.27 / $0.41 | DeepSeek: DeepSeek V3.2 Exp |
| Cache Read Price (per 1M) | $5/1M (50% Off) | $0.135/1M (50% Off) | DeepSeek: DeepSeek V3.2 Exp |
| Context Window / Max Output | 1025K In / 125K Out | 160K In / 144K Out | DeepSeek: DeepSeek V3.2 Exp |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: GPT Astra Latest (-0ms) |
This model always redirects to the latest model in the GPT Astra family.
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
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 Astra Latest to DeepSeek: DeepSeek V3.2 Exp
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 Verified P90 latency of 280ms.