DeepSeek: R1 vs Google: Nano Banana 2.1: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: R1 (deepseek/deepseek-r1) vs Google: Nano Banana 2.1 (google/gemini-nano-banana-2.1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Google: Nano Banana 2.1 (google/gemini-nano-banana-2.1) — 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 (API ID: deepseek/deepseek-r1) vs Google: Nano Banana 2.1 (API ID: google/gemini-nano-banana-2.1), 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). DeepSeek: R1 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 | DeepSeek: R1 | Google: Nano Banana 2.1 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-r1 | google/gemini-nano-banana-2.1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.7 / $2.5 | $1.5 / $7.5 | DeepSeek: R1 |
| Cache Read Price (per 1M) | $0.35/1M (50% Off) | $0.75/1M (50% Off) | DeepSeek: R1 |
| Context Window / Max Output | 63K In / 16K Out | 64K In / 58K Out | Google: Nano Banana 2.1 |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: R1 (-0ms) |
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
Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product reconte
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 to Google: Nano Banana 2.1
Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product reconte Verified P90 latency of 280ms.