Thinking Machines: Inkling Small vs Qwen2.5 72B Instruct: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Thinking Machines: Inkling Small (thinkingmachines/inkling-small) vs Qwen2.5 72B Instruct (qwen/qwen-2.5-72b-instruct). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Thinking Machines: Inkling Small (thinkingmachines/inkling-small) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Thinking Machines: Inkling Small: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.225/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen2.5 72B Instruct (qwen/qwen-2.5-72b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen2.5 72B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.18/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Thinking Machines: Inkling Small (API ID: thinkingmachines/inkling-small) vs Qwen2.5 72B Instruct (API ID: qwen/qwen-2.5-72b-instruct), Qwen2.5 72B Instruct offers lower standard input pricing at $0.36/1M tokens ($0.4/1M output), while Qwen2.5 72B Instruct leads in cached prefix economics at $0.18/1M tokens (50% discount). Thinking Machines: Inkling Small 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 Small | Qwen2.5 72B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | thinkingmachines/inkling-small | qwen/qwen-2.5-72b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.45 / $1.2 | $0.36 / $0.4 | Qwen2.5 72B Instruct |
| Cache Read Price (per 1M) | $0.225/1M (50% Off) | $0.18/1M (50% Off) | Qwen2.5 72B Instruct |
| Context Window / Max Output | 512K In / 256K Out | 32K In / 16K Out | Thinking Machines: Inkling Small |
| P90 First-Token / Edge Latency | 280ms | 280ms | Thinking Machines: Inkling Small (-0ms) |
Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabi
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 Small to Qwen2.5 72B Instruct
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabi Verified P90 latency of 280ms.