Google Gemini 3.1 Pro vs Moonshot Kimi K2.5 (1T MoE): Live Promos, Pricing, Hidden Fees & Latency
Google Gemini 3.1 Pro (gemini-3.1-pro) — Google AI Startup Credits ($350K) & 90% 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.
Moonshot Kimi K2.5 (1T MoE) (kimi-k2.5-1t) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Moonshot Kimi K2.5 (1T MoE): Activate ephemeral prefix caching to slash input costs by 90% (down to 0.055/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Google Gemini 3.1 Pro (API ID: gemini-3.1-pro) vs Moonshot Kimi K2.5 (1T MoE) (API ID: kimi-k2.5-1t), Moonshot Kimi K2.5 (1T MoE) offers lower standard input pricing at $0.55/1M tokens ($2.2/1M output), while Moonshot Kimi K2.5 (1T MoE) leads in cached prefix economics at $0.055/1M tokens (90% discount). Moonshot Kimi K2.5 (1T MoE) achieves a 95ms faster P90 time-to-first-token latency (195ms vs 290ms).
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
| Specification / FinOps Dimension | Google Gemini 3.1 Pro | Moonshot Kimi K2.5 (1T MoE) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | gemini-3.1-pro | kimi-k2.5-1t | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $12 | $0.55 / $2.2 | Moonshot Kimi K2.5 (1T MoE) |
| Cache Read Price (per 1M) | $0.2/1M (90% Off) | $0.055/1M (90% Off) | Moonshot Kimi K2.5 (1T MoE) |
| Context Window / Max Output | 2000K In / 128K Out | 256K In / 128K Out | Google Gemini 3.1 Pro |
| P90 First-Token / Edge Latency | 290ms | 195ms | Moonshot Kimi K2.5 (1T MoE) (-95ms) |
Google 2M context multimodal model (<=200K: $2.00/$12.00, $0.20 cache; >200K cliff: $4.00/$18.00, 180K soft-block).
Moonshot AI 1-Trillion parameter MoE model ($0.55/$2.20 per 1M, $0.055 cache read [90% off], 256K context window).
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 3.1 Pro to Moonshot Kimi K2.5 (1T MoE)
Moonshot AI 1-Trillion parameter MoE model ($0.55/$2.20 per 1M, $0.055 cache read [90% off], 256K context window). Verified P90 latency of 195ms.