Magnum v4 72B vs OpenAI GPT-5.5: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Magnum v4 72B (anthracite-org/magnum-v4-72b) vs OpenAI GPT-5.5 (gpt-5.5). 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.
OpenAI GPT-5.5 (gpt-5.5) 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 Magnum v4 72B (API ID: anthracite-org/magnum-v4-72b) vs OpenAI GPT-5.5 (API ID: gpt-5.5), Magnum v4 72B offers lower standard input pricing at $2.5/1M tokens ($5/1M output), while Magnum v4 72B leads in cached prefix economics at $1.25/1M tokens (50% discount). Magnum v4 72B achieves a 40ms faster P90 time-to-first-token latency (280ms vs 320ms).
Auto-discovered via live global telemetry registry.
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
| Specification / FinOps Dimension | Magnum v4 72B | OpenAI GPT-5.5 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | anthracite-org/magnum-v4-72b | gpt-5.5 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2.5 / $5 | $5 / $30 | Magnum v4 72B |
| Cache Read Price (per 1M) | $1.25/1M (50% Off) | $2.5/1M (50% Off) | Magnum v4 72B |
| Context Window / Max Output | 32K In / 4K Out | 1000K In / 128K Out | OpenAI GPT-5.5 |
| P90 First-Token / Edge Latency | 280ms | 320ms | Magnum v4 72B (-40ms) |
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
Flagship GPT-5 series general model with configurable reasoning_effort from none to xhigh.
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 OpenAI GPT-5.5
Flagship GPT-5 series general model with configurable reasoning_effort from none to xhigh. Verified P90 latency of 320ms.