MiniMax: MiniMax M2-her vs Google: Gemini 3.1 Pro Preview: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MiniMax: MiniMax M2-her (minimax/minimax-m2-her) vs Google: Gemini 3.1 Pro Preview (google/gemini-3.1-pro-preview). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MiniMax: MiniMax M2-her (minimax/minimax-m2-her) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MiniMax: MiniMax M2-her: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.15/1M) or route via asynchronous Batch API for 50% off standard token rates.
Google: Gemini 3.1 Pro Preview (google/gemini-3.1-pro-preview) — 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 MiniMax: MiniMax M2-her (API ID: minimax/minimax-m2-her) vs Google: Gemini 3.1 Pro Preview (API ID: google/gemini-3.1-pro-preview), MiniMax: MiniMax M2-her offers lower standard input pricing at $0.3/1M tokens ($1.2/1M output), while MiniMax: MiniMax M2-her leads in cached prefix economics at $0.15/1M tokens (50% discount). MiniMax: MiniMax M2-her 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 | MiniMax: MiniMax M2-her | Google: Gemini 3.1 Pro Preview | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | minimax/minimax-m2-her | google/gemini-3.1-pro-preview | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.3 / $1.2 | $2 / $12 | MiniMax: MiniMax M2-her |
| Cache Read Price (per 1M) | $0.15/1M (50% Off) | $1/1M (50% Off) | MiniMax: MiniMax M2-her |
| Context Window / Max Output | 64K In / 2K Out | 1024K In / 64K Out | Google: Gemini 3.1 Pro Preview |
| P90 First-Token / Edge Latency | 280ms | 280ms | MiniMax: MiniMax M2-her (-0ms) |
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in
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 MiniMax: MiniMax M2-her to Google: Gemini 3.1 Pro Preview
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.