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inclusionAI
inclusionai/ling-3.0-flashCatalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
inclusionAI 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 production-scale agentic inference* as key priorities, enabling developers...
Ling 3.0 Flash earns a request when it needs step-by-step reasoning, tool calls, very long inputs; a short, general request would go to MiniMax M3.1 Flash (free) instead - free per million input tokens against $0.02 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points.
Nothing on this deployment answers as this model yet. Connect your own provider under Model providers, or add a target to your catalogue - the router picks it up without retraining.
# targets.yaml - declare a target that runs Ling 3.0 Flash
targets:
- id: ling-3-0-flash
kind: llm
name: Ling 3.0 Flash
metadata:
model: inclusionai/ling-3.0-flash # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 262144
cost:
usd_per_1k_tokens: 0.000042Input list price per million tokens; Ling 3.0 Flash is the cheapest of 3 listed.
Photo: RDNE Stock project
Cached input reads $0.004 per 1M · weights on Hugging Face as inclusionAI/Ling-3.0-flash
A higher intelligence index, best first, with the price it comes at.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.