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Favicon for Io Net

io.net

Browse models provided by io.net (Terms of Service)

5 models

Tokens processed on OpenRouter

  • Favicon for nvidia
    NVIDIA: Nemotron 3.5 Super VLNemotron 3.5 Super VL
    40% off

    NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video as input and returns text, and is built for long-running agents that combine visual understanding with reasoning and tool use. It uses a hybrid Mamba-Transformer architecture with multi-token prediction and supports a 1M-token context. Typical uses include document intelligence, web research, coding validation, customer service, and video understanding. Reasoning is on by default and can be turned off or given a token budget.

    by nvidiaOct 15, 20261M context$0.09/M input tokens$0.30/M output tokens
  • Favicon for xiaomi
    Xiaomi: MiMo-V2.6-FlashMiMo-V2.6-Flash

    MiMo-V2.6-Flash is an open-source foundation model developed by Xiaomi. Built on a Mixture-of-Experts architecture with 309B total parameters and 15B activated per token, it employs a hybrid attention mechanism for greater computational efficiency. The model features a 1M-token context window and native multimodal capabilities. Optimized for agentic workflows, it delivers strong performance across coding, visual, general, and research scenarios, excelling at complex, long-horizon tasks with robust generalization across a diverse range of agent harnesses.

    by xiaomiSep 21, 20261.05M context$0.10/M input tokens$0.28/M output tokens
  • Favicon for moonshotai
    MoonshotAI: Kimi K3Kimi K3

    Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at navigating large repositories, using tools, debugging, and iterating against images, logs, tests, and runtime feedback. Its architecture uses KDA and Attention Residuals for computational efficiency.

    by moonshotaiJul 16, 20261.05M context$2.30/M input tokens$14/M output tokens
  • Favicon for google
    Google: Gemma 4 26B A4B Gemma 4 26B A4B
    10% off

    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$0.081/M input tokens$0.279/M output tokens
  • Favicon for mistralai
    Mistral: Mistral NemoMistral Nemo
    28% off

    A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi. It supports function calling and is released under the Apache 2.0 license.

    by mistralaiJul 19, 2024131K context$0.01656/M input tokens$0.0216/M output tokens