MiniMax: MiniMax M2 vs OpenAI: gpt-oss-120b (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MiniMax: MiniMax M2 (minimax/minimax-m2) vs OpenAI: gpt-oss-120b (batch) (openai/gpt-oss-120b:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MiniMax: MiniMax M2 (minimax/minimax-m2) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MiniMax: MiniMax M2: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.1275/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI: gpt-oss-120b (batch) (openai/gpt-oss-120b: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).
In Etuki October 2026 FinOps telemetry comparing MiniMax: MiniMax M2 (API ID: minimax/minimax-m2) vs OpenAI: gpt-oss-120b (batch) (API ID: openai/gpt-oss-120b:batch), OpenAI: gpt-oss-120b (batch) offers lower standard input pricing at $0.0296/1M tokens ($0.136/1M output), while OpenAI: gpt-oss-120b (batch) leads in cached prefix economics at $0.0148/1M tokens (50% discount). MiniMax: MiniMax M2 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 | MiniMax: MiniMax M2 | OpenAI: gpt-oss-120b (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | minimax/minimax-m2 | openai/gpt-oss-120b:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.255 / $1.02 | $0.0296 / $0.136 | OpenAI: gpt-oss-120b (batch) |
| Cache Read Price (per 1M) | $0.1275/1M (50% Off) | $0.0148/1M (50% Off) | OpenAI: gpt-oss-120b (batch) |
| Context Window / Max Output | 200K In / 128K Out | 128K In / 115K Out | MiniMax: MiniMax M2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | MiniMax: MiniMax M2 (-0ms) |
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it de
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. I
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 MiniMax: MiniMax M2 to OpenAI: gpt-oss-120b (batch)
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. I Verified P90 latency of 280ms.