Inception: Mercury 3 vs Google Gemini 2.5 Pro Batch: Live Promos, Pricing, Hidden Fees & Latency
Inception: Mercury 3 (inception/mercury-3) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Inception: Mercury 3: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
Google Gemini 2.5 Pro Batch (google/gemini-2.5-pro-batch) — Google AI Startup Credits ($350K) & 75% 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 Inception: Mercury 3 (API ID: inception/mercury-3) vs Google Gemini 2.5 Pro Batch (API ID: google/gemini-2.5-pro-batch), Inception: Mercury 3 offers lower standard input pricing at $0.1/1M tokens ($0.35/1M output), while Inception: Mercury 3 leads in cached prefix economics at $0.05/1M tokens (50% discount). Google Gemini 2.5 Pro Batch achieves a 10ms faster P90 time-to-first-token latency (270ms vs 280ms).
Auto-discovered via live global telemetry registry.
Prompts exceeding 200K tokens incur 2x tier pricing unless pinned via Google AI Studio Context Caching (75% off).
| Specification / FinOps Dimension | Inception: Mercury 3 | Google Gemini 2.5 Pro Batch | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | inception/mercury-3 | google/gemini-2.5-pro-batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.35 | $1 / $5 | Inception: Mercury 3 |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $0.25/1M (75% Off) | Inception: Mercury 3 |
| Context Window / Max Output | 977K In / 128K Out | 1000K In / 128K Out | Inception: Mercury 3 |
| P90 First-Token / Edge Latency | 280ms | 270ms | Google Gemini 2.5 Pro Batch (-10ms) |
Mercury 3 is a diffusion-based language model from Inception, and the lab's most capable model to date. It is suited for agentic workflows and real-time applications where latency
Google Gemini 2.5 Pro Batch is Google DeepMind's native multimodal frontier model supporting up to 2M context tokens and implicit context caching.
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 Inception: Mercury 3 to Google Gemini 2.5 Pro Batch
Google Gemini 2.5 Pro Batch is Google DeepMind's native multimodal frontier model supporting up to 2M context tokens and implicit context caching. Verified P90 latency of 270ms.