Qwen: Qwen3.5 397B A17B vs inclusionAI: Ling 3.1 Flash: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.5 397B A17B (qwen/qwen3.5-397b-a17b) vs inclusionAI: Ling 3.1 Flash (inclusionai/ling-3.1-flash). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.5 397B A17B (qwen/qwen3.5-397b-a17b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5 397B A17B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.25/1M) or route via asynchronous Batch API for 50% off standard token rates.
inclusionAI: Ling 3.1 Flash (inclusionai/ling-3.1-flash) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for inclusionAI: Ling 3.1 Flash: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0375/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.5 397B A17B (API ID: qwen/qwen3.5-397b-a17b) vs inclusionAI: Ling 3.1 Flash (API ID: inclusionai/ling-3.1-flash), inclusionAI: Ling 3.1 Flash offers lower standard input pricing at $0.075/1M tokens ($0.225/1M output), while inclusionAI: Ling 3.1 Flash leads in cached prefix economics at $0.0375/1M tokens (50% discount). Qwen: Qwen3.5 397B A17B 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 | Qwen: Qwen3.5 397B A17B | inclusionAI: Ling 3.1 Flash | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.5-397b-a17b | inclusionai/ling-3.1-flash | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.5 / $3.6 | $0.075 / $0.225 | inclusionAI: Ling 3.1 Flash |
| Cache Read Price (per 1M) | $0.25/1M (50% Off) | $0.0375/1M (50% Off) | inclusionAI: Ling 3.1 Flash |
| Context Window / Max Output | 256K In / 230K Out | 256K In / 230K Out | Qwen: Qwen3.5 397B A17B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.5 397B A17B (-0ms) |
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, ach
Ling 3.1 Flash is a hybrid reasoning mixture-of-experts model from inclusionAI, with 25B active parameters out of 560B total.
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 Qwen: Qwen3.5 397B A17B to inclusionAI: Ling 3.1 Flash
Ling 3.1 Flash is a hybrid reasoning mixture-of-experts model from inclusionAI, with 25B active parameters out of 560B total. Verified P90 latency of 280ms.