OpenAI: o4 Mini (batch) vs MiniMax: MiniMax-01: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: o4 Mini (batch) (openai/o4-mini:batch) vs MiniMax: MiniMax-01 (minimax/minimax-01). 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).
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 OpenAI: o4 Mini (batch) (API ID: openai/o4-mini:batch) 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). 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) | MiniMax: MiniMax-01 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/o4-mini:batch | minimax/minimax-01 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.55 / $2.2 | $0.2 / $1.1 | MiniMax: MiniMax-01 |
| Cache Read Price (per 1M) | $0.275/1M (50% Off) | $0.1/1M (50% Off) | MiniMax: MiniMax-01 |
| Context Window / Max Output | 195K In / 98K Out | 977K In / 879K Out | MiniMax: MiniMax-01 |
| 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
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 OpenAI: o4 Mini (batch) 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.