*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...
Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.
The model record exists, but no source-linked provider offer is available yet.
Submit a sourceRecorded from the source catalog and provider listings.
inclusionai/ling-3.0-flashEvery result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.
ModelBench does not infer quality from price, context size, or model name. When a source publishes a comparable result, it appears here with its version and link.
Read the methodologyField-level changes detected between successful source imports.
This record has not changed within the retained import history.
Every figure on this page traces back to one of these records.
Fetch the complete source-linked model record. No key, no account, no rate-limited tier.
GET https://www.modelbench.lol/api/v1/models/inclusionai/ling-3.0-flashcurl "https://www.modelbench.lol/api/v1/models/inclusionai/ling-3.0-flash"Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.
*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. It is published by Inclusionai and catalogued here from OpenRouter.
Ling-3.0-flash accepts up to 131.072K tokens of context and returns up to 16.384K output tokens.
Ring-2.6-1T is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational efficiency. It is optimized for coding agents, tool...
inclusionAI: Ling-2.6-1TLing-2.6-1T is an instant (instruct) model from inclusionAI and the company’s trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale. It uses a “fast...
inclusionAI: Ling-2.6-flashLing-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency....
Ling-3.0-flash (free)*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...