OpenRouter Hosts AntLingAGI Ring 2.6 1T for Free Agentic Reasoning

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OpenRouter integrated Ring-2.6-1T, a trillion-parameter reasoning model from AntLingAGI that is free to use through May 15th. The model introduces adjustable thinking effort to balance cognitive depth with token costs, making frontier-level reasoning accessible for production agent workflows.

OpenRouter, a unified API for accessing hundreds of language models, integrated Ring-2.6-1T from AntLingAGI, the foundation model team for Ant Group’s AGI initiative. This trillion-parameter reasoning model uses a Mixture-of-Experts architecture (where only specialized sub-networks activate per request) with 63B active parameters to handle complex, multi-step agent tasks.
Context window
262,144 tokens
Max output
65,536 tokens
Active parameters
63B
Total parameters
1T
Pricing
Free through May 15, 2026
Benchmarks
PinchBench, ClawEval, TAU2-Bench, and others

The release follows OpenRouter's Elephant Alpha launch. Similar to OpenCode's Ring 2.6 integration, the model allows you to toggle between high and extra-high reasoning modes. This flexibility helps manage the trade-off between cognitive depth and execution speed in autonomous systems.

You can deploy the model for long-horizon tasks like automated software engineering using its 262,144-token context window. It is free on the platform through May 15, 2026, providing a zero-cost window to benchmark its performance against other frontier reasoning models. Access is available via the standard API or private chat.

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In case you missed it: Ring-2.6-1T from @AntLingAGI is live and free on OpenRouter through May 15th! A 1T-param thinking model with adjustable thinking effort, capable of tackling your production agent needs.

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Still wondering? A few quick answers below.

Ring-2.6-1T is a trillion-parameter-scale reasoning model developed by AntLingAGI, the AGI initiative of Ant Group. It uses a Mixture-of-Experts architecture with 63 billion active parameters, meaning only a fraction of the model runs for each request. It is specifically designed for complex agentic workflows, such as autonomous coding and multi-step tool execution.

This model features a dynamic compute mechanism that allows users to toggle between high and extra-high reasoning modes. By adjusting the thinking effort, developers can balance cognitive depth against token costs and execution speed. This adaptive reasoning budget is optimized for tool-heavy and multi-turn agent workflows where task complexity varies significantly between steps.

Ring-2.6-1T is currently available for free on the OpenRouter platform through May 15, 2026. During this promotional period, there are no costs for input or output tokens. This allows developers to test the model's trillion-parameter reasoning capabilities in production-grade agent environments and long-horizon coding tasks without incurring standard API inference fees.

The model supports a context window of 262,144 tokens and can generate a maximum output of 65,536 tokens in a single response. It is built on a trillion-parameter scale with 63 billion active parameters. It also supports reasoning tokens, which represent the model's internal thinking process, and can be monitored using specific API parameters on OpenRouter.

Ring-2.6-1T is optimized for real-world agent tasks and has delivered leading results on several specialized benchmarks. These include PinchBench and ClawEval for agentic performance, TAU2-Bench for tool use, and GAIA2-search for complex information retrieval. These scores indicate the model is particularly effective for advanced coding agents and large-scale autonomous systems requiring high execution quality.

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