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Models

6models/ 200

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inclusionAI: Ling 3.0 Flash VL

Input $0.06/1MOutput $0.18/1M

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 and advanced visual agent capabilities. Hybrid instant/reasoning model with tool calling.

by inclusionai·131.1K context·1 provider

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inclusionAI: Ling 3.0 Flash Fin

Input $0.06/1MOutput $0.18/1M

Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment workflows that require complex multi-step tasks and long-horizon planning and execution, while retaining general capabilities in reasoning, coding, and mathematics.

by inclusionai·262.1K context·1 provider

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inclusionAI: Ling 3.0 Flash

Input $0.021/1MOutput $0.063/1M

*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 to complete more useful work within constrained token, latency, and serving-cost budgets.

by inclusionai·262.1K context·1 provider

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inclusionAI: Ring-2.6-1T

Input $0.075/1MOutput $0.625/1M

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 use, and long-horizon task execution, delivering leading results on benchmarks including PinchBench, ClawEval, TAU2-Bench, and GAIA2-search. With adaptive reasoning effort across high and xhigh modes, Ring-2.6-1T dynamically allocates reasoning budget based on task complexity. This enables stronger performance with lower token overhead, especially in tool-heavy and multi-turn agent workflows. Ring-2.6-1T is designed for advanced coding agents, complex reasoning pipelines, and large-scale autonomous systems where execution quality, latency, and cost efficiency all matter.

by inclusionai·262.1K context·1 provider

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inclusionAI: Ling-2.6-1T

Input $0.075/1MOutput $0.625/1M

Ling-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 thinking” approach to reduce costs to roughly a quarter of comparable models while maintaining top-tier performance. The model achieves state-of-the-art results on benchmarks such as AIME26 and SWE-bench Verified, and is well suited for advanced coding, complex reasoning, and large-scale agent workflows where both capability and efficiency are critical.

by inclusionai·262.1K context·1 provider

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inclusionAI: Ling-2.6-flash

Input $0.01/1MOutput $0.03/1M

Ling-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. It delivers performance comparable to state-of-the-art models at a similar scale while significantly reducing token usage across coding, document processing, and lightweight agent workflows.

by inclusionai·262.1K context·1 provider