OpenAI: GPT-4 Turbo vs DeepSeek: R1: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: GPT-4 Turbo (openai/gpt-4-turbo) vs DeepSeek: R1 (deepseek/deepseek-r1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: GPT-4 Turbo (openai/gpt-4-turbo) 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: R1 (deepseek/deepseek-r1) — Automatic Disk KV Cache ($0.35/1M) & 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-4 Turbo (API ID: openai/gpt-4-turbo) vs DeepSeek: R1 (API ID: deepseek/deepseek-r1), DeepSeek: R1 offers lower standard input pricing at $0.7/1M tokens ($2.5/1M output), while DeepSeek: R1 leads in cached prefix economics at $0.35/1M tokens (50% discount). OpenAI: GPT-4 Turbo 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-4 Turbo | DeepSeek: R1 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/gpt-4-turbo | deepseek/deepseek-r1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $10 / $30 | $0.7 / $2.5 | DeepSeek: R1 |
| Cache Read Price (per 1M) | $5/1M (50% Off) | $0.35/1M (50% Off) | DeepSeek: R1 |
| Context Window / Max Output | 125K In / 4K Out | 63K In / 16K Out | DeepSeek: R1 |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: GPT-4 Turbo (-0ms) |
The latest GPT-4 Turbo model with vision capabilities. Vision requests can now use JSON mode and function calling. Training data: up to December 2023.
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inf
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-4 Turbo to DeepSeek: R1
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inf Verified P90 latency of 280ms.