inclusionAI: Ling 3.0 Flash VL vs Qwen: Qwen2.5 7B Instruct: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing inclusionAI: Ling 3.0 Flash VL (inclusionai/ling-3.0-flash-vl) vs Qwen: Qwen2.5 7B Instruct (qwen/qwen-2.5-7b-instruct). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
inclusionAI: Ling 3.0 Flash VL (inclusionai/ling-3.0-flash-vl) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for inclusionAI: Ling 3.0 Flash VL: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.03/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen: Qwen2.5 7B Instruct (qwen/qwen-2.5-7b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen2.5 7B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing inclusionAI: Ling 3.0 Flash VL (API ID: inclusionai/ling-3.0-flash-vl) vs Qwen: Qwen2.5 7B Instruct (API ID: qwen/qwen-2.5-7b-instruct), inclusionAI: Ling 3.0 Flash VL offers lower standard input pricing at $0.06/1M tokens ($0.18/1M output), while inclusionAI: Ling 3.0 Flash VL leads in cached prefix economics at $0.03/1M tokens (50% discount). inclusionAI: Ling 3.0 Flash VL 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 VL | Qwen: Qwen2.5 7B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | inclusionai/ling-3.0-flash-vl | qwen/qwen-2.5-7b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.06 / $0.18 | $0.1 / $0.2 | inclusionAI: Ling 3.0 Flash VL |
| Cache Read Price (per 1M) | $0.03/1M (50% Off) | $0.05/1M (50% Off) | inclusionAI: Ling 3.0 Flash VL |
| Context Window / Max Output | 128K In / 32K Out | 32K In / 29K Out | inclusionAI: Ling 3.0 Flash VL |
| P90 First-Token / Edge Latency | 280ms | 280ms | inclusionAI: Ling 3.0 Flash VL (-0ms) |
Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception an
Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabil
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 VL to Qwen: Qwen2.5 7B Instruct
Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabil Verified P90 latency of 280ms.