DeepSeek: DeepSeek V3.1 vs OpenAI GPT-5.3-Codex: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V3.1 (deepseek/deepseek-chat-v3.1) vs OpenAI GPT-5.3-Codex (gpt-5.3-codex). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek V3.1 (deepseek/deepseek-chat-v3.1) — Automatic Disk KV Cache ($0.125/1M) & 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-5.3-Codex (gpt-5.3-codex) 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 V3.1 (API ID: deepseek/deepseek-chat-v3.1) vs OpenAI GPT-5.3-Codex (API ID: gpt-5.3-codex), DeepSeek: DeepSeek V3.1 offers lower standard input pricing at $0.25/1M tokens ($0.95/1M output), while DeepSeek: DeepSeek V3.1 leads in cached prefix economics at $0.125/1M tokens (50% discount). OpenAI GPT-5.3-Codex achieves a 30ms faster P90 time-to-first-token latency (250ms vs 280ms).
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 | DeepSeek: DeepSeek V3.1 | OpenAI GPT-5.3-Codex | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-chat-v3.1 | gpt-5.3-codex | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.25 / $0.95 | $1.75 / $14 | DeepSeek: DeepSeek V3.1 |
| Cache Read Price (per 1M) | $0.125/1M (50% Off) | $0.875/1M (50% Off) | DeepSeek: DeepSeek V3.1 |
| Context Window / Max Output | 160K In / 32K Out | 1000K In / 128K Out | OpenAI GPT-5.3-Codex |
| P90 First-Token / Edge Latency | 280ms | 250ms | OpenAI GPT-5.3-Codex (-30ms) |
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 ba
Dedicated agentic software engineering model tuned for multi-hour terminal and IDE sessions.
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 V3.1 to OpenAI GPT-5.3-Codex
Dedicated agentic software engineering model tuned for multi-hour terminal and IDE sessions. Verified P90 latency of 250ms.