Google: Gemini 3.1 Pro Preview (batch) vs Inference.net: Schematron V2 Small: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Google: Gemini 3.1 Pro Preview (batch) (google/gemini-3.1-pro-preview:batch) vs Inference.net: Schematron V2 Small (inference-net/schematron-v2-small). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
Inference.net: Schematron V2 Small (inference-net/schematron-v2-small) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Inference.net: Schematron V2 Small: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.025/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Google: Gemini 3.1 Pro Preview (batch) (API ID: google/gemini-3.1-pro-preview:batch) vs Inference.net: Schematron V2 Small (API ID: inference-net/schematron-v2-small), Inference.net: Schematron V2 Small offers lower standard input pricing at $0.05/1M tokens ($0.23/1M output), while Inference.net: Schematron V2 Small leads in cached prefix economics at $0.025/1M tokens (50% discount). Google: Gemini 3.1 Pro Preview (batch) 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 3.1 Pro Preview (batch) | Inference.net: Schematron V2 Small | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | google/gemini-3.1-pro-preview:batch | inference-net/schematron-v2-small | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $6 | $0.05 / $0.23 | Inference.net: Schematron V2 Small |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.025/1M (50% Off) | Inference.net: Schematron V2 Small |
| Context Window / Max Output | 1024K In / 64K Out | 125K In / 4K Out | Google: Gemini 3.1 Pro Preview (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Google: Gemini 3.1 Pro Preview (batch) (-0ms) |
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
Schematron V2 Small is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes extraction quality for complex schemas and long pages. Extraction instruction
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 Preview (batch) to Inference.net: Schematron V2 Small
Schematron V2 Small is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes extraction quality for complex schemas and long pages. Extraction instruction Verified P90 latency of 280ms.