Magnum v4 72B vs MiniMax: MiniMax M2-her: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Magnum v4 72B (anthracite-org/magnum-v4-72b) vs MiniMax: MiniMax M2-her (minimax/minimax-m2-her). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Magnum v4 72B (anthracite-org/magnum-v4-72b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Magnum v4 72B: Activate ephemeral prefix caching to slash input costs by 50% (down to $1.25/1M) or route via asynchronous Batch API for 50% off standard token rates.
MiniMax: MiniMax M2-her (minimax/minimax-m2-her) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MiniMax: MiniMax M2-her: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.15/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Magnum v4 72B (API ID: anthracite-org/magnum-v4-72b) vs MiniMax: MiniMax M2-her (API ID: minimax/minimax-m2-her), MiniMax: MiniMax M2-her offers lower standard input pricing at $0.3/1M tokens ($1.2/1M output), while MiniMax: MiniMax M2-her leads in cached prefix economics at $0.15/1M tokens (50% discount). Magnum v4 72B 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 | Magnum v4 72B | MiniMax: MiniMax M2-her | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | anthracite-org/magnum-v4-72b | minimax/minimax-m2-her | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2.5 / $5 | $0.3 / $1.2 | MiniMax: MiniMax M2-her |
| Cache Read Price (per 1M) | $1.25/1M (50% Off) | $0.15/1M (50% Off) | MiniMax: MiniMax M2-her |
| Context Window / Max Output | 32K In / 4K Out | 64K In / 2K Out | Magnum v4 72B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Magnum v4 72B (-0ms) |
This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet(https://openrouter.ai/anthropic/claude-3.5-sonnet) and Opus(https://o
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent 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 Magnum v4 72B to MiniMax: MiniMax M2-her
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in Verified P90 latency of 280ms.