inclusionAI: Ling 3.0 Flash vs XingChen: Xing4.0 29B A4B (free): Live Promos, Pricing, Hidden Fees & Latency
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.
XingChen: Xing4.0 29B A4B (free) (xingchen-agi/xing4.0-29b-a4b:free) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for XingChen: Xing4.0 29B A4B (free): Activate ephemeral prefix caching to slash input costs by 50% (down to 0/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing inclusionAI: Ling 3.0 Flash (API ID: inclusionai/ling-3.0-flash) vs XingChen: Xing4.0 29B A4B (free) (API ID: xingchen-agi/xing4.0-29b-a4b:free), XingChen: Xing4.0 29B A4B (free) offers lower standard input pricing at $0/1M tokens ($0/1M output), while XingChen: Xing4.0 29B A4B (free) leads in cached prefix economics at $0/1M tokens (50% discount). inclusionAI: Ling 3.0 Flash 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 | inclusionAI: Ling 3.0 Flash | XingChen: Xing4.0 29B A4B (free) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | inclusionai/ling-3.0-flash | xingchen-agi/xing4.0-29b-a4b:free | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.021 / $0.063 | $0 / $0 | XingChen: Xing4.0 29B A4B (free) |
| Cache Read Price (per 1M) | $0.0105/1M (50% Off) | $0/1M (50% Off) | XingChen: Xing4.0 29B A4B (free) |
| Context Window / Max Output | 256K In / 32K Out | 256K In / 230K Out | XingChen: Xing4.0 29B A4B (free) |
| P90 First-Token / Edge Latency | 280ms | 280ms | inclusionAI: Ling 3.0 Flash (-0ms) |
*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
Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with
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 inclusionAI: Ling 3.0 Flash to XingChen: Xing4.0 29B A4B (free)
Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with Verified P90 latency of 280ms.