OpenAI: gpt-oss-120b vs DeepSeek: DeepSeek V3.2: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: gpt-oss-120b (openai/gpt-oss-120b) vs DeepSeek: DeepSeek V3.2 (deepseek/deepseek-v3.2). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: gpt-oss-120b (openai/gpt-oss-120b) 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 (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.
In Etuki October 2026 FinOps telemetry comparing OpenAI: gpt-oss-120b (API ID: openai/gpt-oss-120b) vs DeepSeek: DeepSeek V3.2 (API ID: deepseek/deepseek-v3.2), OpenAI: gpt-oss-120b offers lower standard input pricing at $0.15/1M tokens ($0.6/1M output), while OpenAI: gpt-oss-120b leads in cached prefix economics at $0.075/1M tokens (50% discount). OpenAI: gpt-oss-120b 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-oss-120b | DeepSeek: DeepSeek V3.2 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/gpt-oss-120b | deepseek/deepseek-v3.2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.15 / $0.6 | $0.259 / $0.8 | OpenAI: gpt-oss-120b |
| Cache Read Price (per 1M) | $0.075/1M (50% Off) | $0.1295/1M (50% Off) | OpenAI: gpt-oss-120b |
| Context Window / Max Output | 128K In / 64K Out | 160K In / 144K Out | DeepSeek: DeepSeek V3.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: gpt-oss-120b (-0ms) |
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. I
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
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-oss-120b to DeepSeek: DeepSeek V3.2
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 Verified P90 latency of 280ms.