Thinking Machines: Inkling vs Microsoft: Phi 4: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Thinking Machines: Inkling (thinkingmachines/inkling) vs Microsoft: Phi 4 (microsoft/phi-4). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Thinking Machines: Inkling (thinkingmachines/inkling) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Thinking Machines: Inkling: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.5/1M) or route via asynchronous Batch API for 50% off standard token rates.
Microsoft: Phi 4 (microsoft/phi-4) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Microsoft: Phi 4: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.035/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Thinking Machines: Inkling (API ID: thinkingmachines/inkling) vs Microsoft: Phi 4 (API ID: microsoft/phi-4), Microsoft: Phi 4 offers lower standard input pricing at $0.07/1M tokens ($0.14/1M output), while Microsoft: Phi 4 leads in cached prefix economics at $0.035/1M tokens (50% discount). Thinking Machines: Inkling 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 | Thinking Machines: Inkling | Microsoft: Phi 4 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | thinkingmachines/inkling | microsoft/phi-4 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $4.05 | $0.07 / $0.14 | Microsoft: Phi 4 |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.035/1M (50% Off) | Microsoft: Phi 4 |
| Context Window / Max Output | 512K In / 461K Out | 16K In / 14K Out | Thinking Machines: Inkling |
| P90 First-Token / Edge Latency | 280ms | 280ms | Thinking Machines: Inkling (-0ms) |
Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning
[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses
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 Thinking Machines: Inkling to Microsoft: Phi 4
[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses Verified P90 latency of 280ms.