MiniMax: MiniMax M1 vs Qwen: Qwen3.8 Max (0902): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MiniMax: MiniMax M1 (minimax/minimax-m1) vs Qwen: Qwen3.8 Max (0902) (qwen/qwen3.8-max-0902). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MiniMax: MiniMax M1 (minimax/minimax-m1) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MiniMax: MiniMax M1: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.275/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen: Qwen3.8 Max (0902) (qwen/qwen3.8-max-0902) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.8 Max (0902): Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing MiniMax: MiniMax M1 (API ID: minimax/minimax-m1) vs Qwen: Qwen3.8 Max (0902) (API ID: qwen/qwen3.8-max-0902), MiniMax: MiniMax M1 offers lower standard input pricing at $0.55/1M tokens ($2.2/1M output), while MiniMax: MiniMax M1 leads in cached prefix economics at $0.275/1M tokens (50% discount). MiniMax: MiniMax M1 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 M1 | Qwen: Qwen3.8 Max (0902) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | minimax/minimax-m1 | qwen/qwen3.8-max-0902 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.55 / $2.2 | $2 / $6 | MiniMax: MiniMax M1 |
| Cache Read Price (per 1M) | $0.275/1M (50% Off) | $1/1M (50% Off) | MiniMax: MiniMax M1 |
| Context Window / Max Output | 977K In / 39K Out | 977K In / 128K Out | Qwen: Qwen3.8 Max (0902) |
| P90 First-Token / Edge Latency | 280ms | 280ms | MiniMax: MiniMax M1 (-0ms) |
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture pa
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input a
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 M1 to Qwen: Qwen3.8 Max (0902)
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input a Verified P90 latency of 280ms.