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Favicon for Io Net

io.net

Browse models provided by io.net

4 models

Tokens processed on OpenRouter

  • 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$0.80/M input tokens$4/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$1.06/M input tokens$4.40/M output tokens
  • Favicon for google
    Google: Gemma 4 26B A4B Gemma 4 26B A4B

    Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at a fraction of the compute cost. Supports multimodal input including text, images, and video (up to 60s at 1fps). Features a 256K token context window, native function calling, configurable thinking/reasoning mode, and structured output support. Released under Apache 2.0.

    by googleApr 3, 2026262K context$0.09/M input tokens$0.40/M output tokens
  • Favicon for openai
    OpenAI: gpt-oss-120bgpt-oss-120b

    gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized to run on a single H100 GPU with native MXFP4 quantization. The model supports configurable reasoning depth, full chain-of-thought access, and native tool use, including function calling, browsing, and structured output generation.

    by openaiAug 5, 2025131K context$0.1575/M input tokens$0.351/M output tokens