OpenAI: o4 Mini (batch) vs Google: Gemma 4 31B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: o4 Mini (batch) (openai/o4-mini:batch) vs Google: Gemma 4 31B (google/gemma-4-31b-it). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: o4 Mini (batch) (openai/o4-mini:batch) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 75% automatic prefix caching ($0.50/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
Google: Gemma 4 31B (google/gemma-4-31b-it) — 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 OpenAI: o4 Mini (batch) (API ID: openai/o4-mini:batch) vs Google: Gemma 4 31B (API ID: google/gemma-4-31b-it), Google: Gemma 4 31B offers lower standard input pricing at $0.2/1M tokens ($0.4/1M output), while Google: Gemma 4 31B leads in cached prefix economics at $0.1/1M tokens (50% discount). OpenAI: o4 Mini (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 | OpenAI: o4 Mini (batch) | Google: Gemma 4 31B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/o4-mini:batch | google/gemma-4-31b-it | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.55 / $2.2 | $0.2 / $0.4 | Google: Gemma 4 31B |
| Cache Read Price (per 1M) | $0.275/1M (50% Off) | $0.1/1M (50% Off) | Google: Gemma 4 31B |
| Context Window / Max Output | 195K In / 98K Out | 256K In / 16K Out | OpenAI: o4 Mini (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: o4 Mini (batch) (-0ms) |
OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking
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 OpenAI: o4 Mini (batch) to Google: Gemma 4 31B
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking Verified P90 latency of 280ms.