inclusionAI: Ling 3.0 Flash vs Meta: Llama 3.1 70B Instruct: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing inclusionAI: Ling 3.0 Flash (inclusionai/ling-3.0-flash) vs Meta: Llama 3.1 70B Instruct (meta-llama/llama-3.1-70b-instruct). Simulate cache read multipliers, context cliffs, MAU bills, and P90 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.
Meta: Llama 3.1 70B Instruct (meta-llama/llama-3.1-70b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 3.1 70B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.2/1M) 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 Meta: Llama 3.1 70B Instruct (API ID: meta-llama/llama-3.1-70b-instruct), 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). 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 | Meta: Llama 3.1 70B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | inclusionai/ling-3.0-flash | meta-llama/llama-3.1-70b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.021 / $0.063 | $0.4 / $0.4 | inclusionAI: Ling 3.0 Flash |
| Cache Read Price (per 1M) | $0.0105/1M (50% Off) | $0.2/1M (50% Off) | inclusionAI: Ling 3.0 Flash |
| Context Window / Max Output | 256K In / 32K Out | 128K In / 16K Out | inclusionAI: Ling 3.0 Flash |
| 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
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonst
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 Meta: Llama 3.1 70B Instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonst Verified P90 latency of 280ms.