xAI Grok 4.7 vs Google Gemini 3.1 Pro: Live Promos, Pricing, Hidden Fees & Latency
xAI Grok 4.7 (grok-4.7) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for xAI Grok 4.7: Activate ephemeral prefix caching to slash input costs by 75% (down to 0.5/1M) or route via asynchronous Batch API for 50% off standard token rates.
Google Gemini 3.1 Pro (gemini-3.1-pro) — Google AI Startup Credits ($350K) & 90% 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 xAI Grok 4.7 (API ID: grok-4.7) vs Google Gemini 3.1 Pro (API ID: gemini-3.1-pro), xAI Grok 4.7 offers lower standard input pricing at $2/1M tokens ($6/1M output), while Google Gemini 3.1 Pro leads in cached prefix economics at $0.2/1M tokens (90% discount). xAI Grok 4.7 achieves a 160ms faster P90 time-to-first-token latency (130ms vs 290ms).
<200K: $2.00/$6.00 ($0.50 cache); >=200K (including cached tokens) full-request 2x cliff: $4.00/$12.00 ($1.00 cache). Not eligible for Batch discount (0%); Priority 2x; US endpoint +10%.
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
| Specification / FinOps Dimension | xAI Grok 4.7 | Google Gemini 3.1 Pro | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | grok-4.7 | gemini-3.1-pro | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $6 | $2 / $12 | xAI Grok 4.7 |
| Cache Read Price (per 1M) | $0.5/1M (75% Off) | $0.2/1M (90% Off) | Google Gemini 3.1 Pro |
| Context Window / Max Output | 500K In / 128K Out | 2000K In / 128K Out | xAI Grok 4.7 |
| P90 First-Token / Edge Latency | 130ms | 290ms | xAI Grok 4.7 (-160ms) |
xAI frontier reasoning & coding model (500K context): <200K at $2/$6 ($0.50 cache); >=200K at $4/$12 ($1.00 cache). No batch discount.
Google 2M context multimodal model (<=200K: $2.00/$12.00, $0.20 cache; >200K cliff: $4.00/$18.00, 180K soft-block).
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 xAI Grok 4.7 to Google Gemini 3.1 Pro
Google 2M context multimodal model (<=200K: $2.00/$12.00, $0.20 cache; >200K cliff: $4.00/$18.00, 180K soft-block). Verified P90 latency of 290ms.