DeepSeek-R1 (Reasoner) vs Google: Gemini 3.1 Pro Preview (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek-R1 (Reasoner) (deepseek-reasoner) vs Google: Gemini 3.1 Pro Preview (batch) (google/gemini-3.1-pro-preview:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek-R1 (Reasoner) (deepseek-reasoner) — Automatic Disk KV Cache ($0.275/1M) & 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.
Google: Gemini 3.1 Pro Preview (batch) (google/gemini-3.1-pro-preview:batch) — Google AI Startup Credits ($350K) & 50% Cache Promo
Google DeepMind is currently subsidizing Gemini 4 Argon at 50% off standard rates ($2.00/1M input & $10.00/1M output instead of $4/$20) until November 30, 2026, alongside 95% off Context Caching ($0.10/1M) and up to $350,000 in Google for Startups Cloud/Vertex AI credits.
In Etuki October 2026 FinOps telemetry comparing DeepSeek-R1 (Reasoner) (API ID: deepseek-reasoner) vs Google: Gemini 3.1 Pro Preview (batch) (API ID: google/gemini-3.1-pro-preview:batch), DeepSeek-R1 (Reasoner) offers lower standard input pricing at $0.55/1M tokens ($2.19/1M output), while DeepSeek-R1 (Reasoner) leads in cached prefix economics at $0.275/1M tokens (50% discount). Google: Gemini 3.1 Pro Preview (batch) achieves a 260ms faster P90 time-to-first-token latency (280ms vs 540ms).
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | DeepSeek-R1 (Reasoner) | Google: Gemini 3.1 Pro Preview (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek-reasoner | google/gemini-3.1-pro-preview:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.55 / $2.19 | $1 / $6 | DeepSeek-R1 (Reasoner) |
| Cache Read Price (per 1M) | $0.275/1M (50% Off) | $0.5/1M (50% Off) | DeepSeek-R1 (Reasoner) |
| Context Window / Max Output | 400K In / 128K Out | 1024K In / 64K Out | DeepSeek-R1 (Reasoner) |
| P90 First-Token / Edge Latency | 540ms | 280ms | Google: Gemini 3.1 Pro Preview (batch) (-260ms) |
Open-weight reinforcement-learning reasoning model for formal math, finance, and theorem synthesis.
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage acro
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-R1 (Reasoner) to Google: Gemini 3.1 Pro Preview (batch)
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage acro Verified P90 latency of 280ms.