MoonshotAI: Kimi K2 0905 vs Google: Gemini 3.1 Pro Preview (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MoonshotAI: Kimi K2 0905 (moonshotai/kimi-k2-0905) 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.
MoonshotAI: Kimi K2 0905 (moonshotai/kimi-k2-0905) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K2 0905: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.3/1M) or route via asynchronous Batch API for 50% off standard token rates.
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 MoonshotAI: Kimi K2 0905 (API ID: moonshotai/kimi-k2-0905) vs Google: Gemini 3.1 Pro Preview (batch) (API ID: google/gemini-3.1-pro-preview:batch), MoonshotAI: Kimi K2 0905 offers lower standard input pricing at $0.6/1M tokens ($2.5/1M output), while MoonshotAI: Kimi K2 0905 leads in cached prefix economics at $0.3/1M tokens (50% discount). MoonshotAI: Kimi K2 0905 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 | MoonshotAI: Kimi K2 0905 | Google: Gemini 3.1 Pro Preview (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | moonshotai/kimi-k2-0905 | google/gemini-3.1-pro-preview:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.6 / $2.5 | $1 / $6 | MoonshotAI: Kimi K2 0905 |
| Cache Read Price (per 1M) | $0.3/1M (50% Off) | $0.5/1M (50% Off) | MoonshotAI: Kimi K2 0905 |
| Context Window / Max Output | 256K In / 96K Out | 1024K In / 64K Out | MoonshotAI: Kimi K2 0905 |
| P90 First-Token / Edge Latency | 280ms | 280ms | MoonshotAI: Kimi K2 0905 (-0ms) |
Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trilli
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 MoonshotAI: Kimi K2 0905 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.