Qwen: Qwen3.8 2.4T A95B vs inclusionAI: Ling 3.0 Flash: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b) vs inclusionAI: Ling 3.0 Flash (inclusionai/ling-3.0-flash). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.8 2.4T A95B: Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
inclusionAI: Ling 3.0 Flash (inclusionai/ling-3.0-flash) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for inclusionAI: Ling 3.0 Flash: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0105/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.8 2.4T A95B (API ID: qwen/qwen3.8-2.4t-a95b) vs inclusionAI: Ling 3.0 Flash (API ID: inclusionai/ling-3.0-flash), inclusionAI: Ling 3.0 Flash offers lower standard input pricing at $0.021/1M tokens ($0.063/1M output), while inclusionAI: Ling 3.0 Flash leads in cached prefix economics at $0.0105/1M tokens (50% discount). Qwen: Qwen3.8 2.4T A95B 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: Qwen3.8 2.4T A95B | inclusionAI: Ling 3.0 Flash | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.8-2.4t-a95b | inclusionai/ling-3.0-flash | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $6 | $0.021 / $0.063 | inclusionAI: Ling 3.0 Flash |
| Cache Read Price (per 1M) | $1/1M (50% Off) | $0.0105/1M (50% Off) | inclusionAI: Ling 3.0 Flash |
| Context Window / Max Output | 1024K In / 128K Out | 256K In / 32K Out | Qwen: Qwen3.8 2.4T A95B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.8 2.4T A95B (-0ms) |
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out
*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and pr
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: Qwen3.8 2.4T A95B to inclusionAI: Ling 3.0 Flash
*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and pr Verified P90 latency of 280ms.