Google: Gemini 2.5 Pro vs MiniMax: MiniMax-01: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Google: Gemini 2.5 Pro (google/gemini-2.5-pro) vs MiniMax: MiniMax-01 (minimax/minimax-01). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Google: Gemini 2.5 Pro (google/gemini-2.5-pro) — 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.
MiniMax: MiniMax-01 (minimax/minimax-01) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MiniMax: MiniMax-01: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.1/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Google: Gemini 2.5 Pro (API ID: google/gemini-2.5-pro) vs MiniMax: MiniMax-01 (API ID: minimax/minimax-01), MiniMax: MiniMax-01 offers lower standard input pricing at $0.2/1M tokens ($1.1/1M output), while MiniMax: MiniMax-01 leads in cached prefix economics at $0.1/1M tokens (50% discount). Google: Gemini 2.5 Pro 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 | Google: Gemini 2.5 Pro | MiniMax: MiniMax-01 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | google/gemini-2.5-pro | minimax/minimax-01 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1.25 / $10 | $0.2 / $1.1 | MiniMax: MiniMax-01 |
| Cache Read Price (per 1M) | $0.625/1M (50% Off) | $0.1/1M (50% Off) | MiniMax: MiniMax-01 |
| Context Window / Max Output | 1024K In / 64K Out | 977K In / 879K Out | MiniMax: MiniMax-01 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Google: Gemini 2.5 Pro (-0ms) |
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to
MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per in
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 2.5 Pro to MiniMax: MiniMax-01
MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per in Verified P90 latency of 280ms.