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Favicon for Io Net

io.net

Browse models provided by io.net

5 models

Tokens processed on OpenRouter

  • Favicon for qwen
    Qwen: Qwen3.6 35B A3BQwen3.6 35B A3B

    Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated DeltaNet linear attention with standard gated attention layers, enabling efficient inference at a fraction of the compute cost. The model supports a 262K token native context window (extensible to 1M via YaRN) and accepts text, image, and video inputs. It includes integrated thinking mode with reasoning traces preserved across multi-turn conversations, function calling, and structured output. Released under the Apache 2.0 license.

    by qwenApr 27, 2026262K context$0.15 /M input tokens$1 /M output tokens
  • Favicon for qwen
    Qwen: Qwen3.6 27BQwen3.6 27B

    Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs — and supports a 262,144-token context window. The model is designed for agentic coding and reasoning tasks, with particular strength in repository-level code comprehension, front-end development workflows, and multi-step problem solving. It includes a built-in thinking mode for extended reasoning and preserves thinking context across conversation history. Qwen3.6 27B supports 201 languages and dialects and is released under the Apache 2.0 license.

    by qwenApr 27, 2026262K context$0.317 /M input tokens$3.20 /M output tokens
  • Favicon for moonshotai
    MoonshotAI: Kimi K2.6Kimi K2.6

    Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture scales to hundreds of parallel sub-agents for autonomous task decomposition - delivering documents, websites, and spreadsheets in a single run without human oversight.

    by moonshotaiApr 20, 2026262K context$0.73 /M input tokens$3.49 /M output tokens
  • Favicon for z-ai
    Z.ai: GLM 5.1GLM 5.1

    GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on a single task for more than 8 hours, autonomously planning, executing, and improving itself throughout the process, ultimately delivering complete, engineering-grade results.

    by z-aiApr 7, 2026203K context$1.22 /M input tokens$4.08 /M output tokens
  • Favicon for z-ai
    Z.ai: GLM 4.5 AirGLM 4.5 Air

    GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter size. GLM-4.5-Air also supports hybrid inference modes, offering a "thinking mode" for advanced reasoning and tool use, and a "non-thinking mode" for real-time interaction. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config)

    by z-aiJul 25, 2025131K context$0.125 /M input tokens$0.84 /M output tokens