Google: Gemini Flash Latest vs DeepSeek-R1 (Reasoner): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Google: Gemini Flash Latest (~google/gemini-flash-latest) vs DeepSeek-R1 (Reasoner) (deepseek-reasoner). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Google: Gemini Flash Latest (~google/gemini-flash-latest) — 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.
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.
In Etuki October 2026 FinOps telemetry comparing Google: Gemini Flash Latest (API ID: ~google/gemini-flash-latest) vs DeepSeek-R1 (Reasoner) (API ID: deepseek-reasoner), 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 Flash Latest achieves a 260ms faster P90 time-to-first-token latency (280ms vs 540ms).
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 | Google: Gemini Flash Latest | DeepSeek-R1 (Reasoner) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | ~google/gemini-flash-latest | deepseek-reasoner | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.75 / $3.75 | $0.55 / $2.19 | DeepSeek-R1 (Reasoner) |
| Cache Read Price (per 1M) | $0.375/1M (50% Off) | $0.275/1M (50% Off) | DeepSeek-R1 (Reasoner) |
| Context Window / Max Output | 1024K In / 64K Out | 400K In / 128K Out | DeepSeek-R1 (Reasoner) |
| P90 First-Token / Edge Latency | 280ms | 540ms | Google: Gemini Flash Latest (-260ms) |
This model always redirects to the latest model in the Gemini Flash family.
Open-weight reinforcement-learning reasoning model for formal math, finance, and theorem synthesis.
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 Google: Gemini Flash Latest to DeepSeek-R1 (Reasoner)
Open-weight reinforcement-learning reasoning model for formal math, finance, and theorem synthesis. Verified P90 latency of 540ms.