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Documentation Index

Fetch the complete documentation index at: https://io.net/docs/llms.txt

Use this file to discover all available pages before exploring further.

To get started, navigate to the Models tab.
Models Nav Bar Pn

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What you can do on the Models Dashboard:

  • Browse the list of models with their context lenghts and prices.
Model NameDeveloperDescription
deepseek-ai/DeepSeek-R1-0528DeepseekEnhanced model with improved reasoning, inference, and algorithmic post-training optimizations; designed for high-accuracy tasks.
meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8Meta AIMultimodal instruction-tuned model leveraging a mixture-of-experts (MoE) architecture for top-tier performance in both text and image understanding.
gpt-oss-120bOpen AIOpen-weight 117B parameter Mixture-of-Experts model supporting 128k context, advanced reasoning via chain-of-thought, optimized for real-world tool use, coding, and efficient local or cloud deployment.
Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-arQwenHigh-capacity, instruction-tuned code generation model optimized with INT4 mixed-precision for fast inference, designed for complex programming tasks on Intel hardware.
Qwen3-Next-80B-A3B-InstructQwenHigh-capacity model optimized for instruction following and knowledge-intensive tasks.
gpt-oss-20bOpen AIOpen-source GPT-style model suitable for text generation and general-purpose tasks.
Qwen3-235B-A22B-Thinking-2507QwenPowerful 235B-parameter language model optimized for deep reasoning, planning, and complex multi-step tasks.
Mistral-Nemo-Instruct-2407Mistral AIInstruction-tuned model focusing on efficient reasoning and NLP tasks.
meta-llama/Llama-3.3-70B-InstructMeta AILarge-scale transformer model fine-tuned for instruction-following, aligning responses with human preferences.
mistralai/Mistral-Large-Instruct-2411Mistral AILarge instruction-tuned model offering strong general-purpose reasoning, summarization, and assistant-style responses.
Qwen/Qwen2.5-VL-32B-InstructQwenPowerful vision-language model trained to follow multimodal instructions, suitable for image understanding, captioning, and reasoning.
meta-llama/Llama-3.2-90B-Vision-InstructMeta AIVision-language model with instruction tuning, capable of image analysis, visual Q&A, and multimodal dialogue generation.
BAAI/bge-multilingual-gemma2BAAIMultilingual embedding model optimized for semantic search and retrieval tasks across diverse languages.
zai-org/GLM-4.6Z.AIAdvanced large-language model that expands context capacity to 200K tokens and significantly enhances coding, reasoning, and agentic capabilities. It excels in real-world coding tools, delivering more natural, human-aligned outputs.
zai-org/GLM-4.7Z.AIAdvanced large-language model that retains a 200K-token context window and elevates coding, reasoning, and agentic capabilities with enhanced multi-step execution and consistency. It introduces sophisticated thinking modes like Preserved Thinking and Turn-level Thinking.
moonshotai/Kimi-K2-Instruct-0905Moonshot AIA state-of-the-art mixture-of-experts (MoE) language model, featuring 32 billion activated parameters and a total of 1 trillion parameters. It delivers exceptional reasoning, coding, and content-generation performance.
moonshotai/Kimi-K2-ThinkingMoonshot AIA high-performance open-source thinking model built for step-by-step thinking and dynamic tool use. It achieves state-of-the-art results on benchmarks such as Humanity’s Last Exam (HLE) and BrowseComp by dramatically scaling multi-step reasoning depth maintaining stable tool-use across 200–300 sequential calls.
deepseek-ai/DeepSeek-V3.2DeepseekA LLM model that combines breakthrough efficiency with exceptional reasoning and tool-use performance. Powered by Sparse Attention and scalable RL post-training, it delivers premium long-context quality at reduced cost. Reports place it in the GPT-5 class with gold-medal wins in the 2025 IMO and IOI.
For a full list of models, visit the AI Models section in your dashboard.

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Testing an AI Model

Before using any of our AI models in your project, you can perform real-time testing directly from the dashboard. This allows you to evaluate the model’s performance and ensure it meets your requirements.

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How to Test an AI Model

  1. Select a Model:
    • Navigate to the Models tab.
    • Select the model you want to test by clicking on it.
  2. Start Testing:
    • On the AI model chat page, type your question or input into the centered text field.
    • Press your Enter key or the arrow icon to submit your query.
      Models Model Chat Pn
      Your Daily Credits usage is shown above the request field. To view detailed model-specific usage information, visit the IO Intelligence Payments page.
  3. Interact with the Model:
    • The AI model will respond, starting a conversation. You can continue testing by asking additional questions or providing more input.
    • Compare different models to find the one that best suits your needs.

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Managing Chats

  • View Previous Chats:
    • On the left, you can manage your previously created chats with different AI models.
    • Click on any chat to dive deeper into the conversation.
  • Create or Remove Chats:
    • Create a new chat by clicking the + button next to the model name.
    • Remove a chat by clicking the three-dot menu and selecting Delete. Remove unnecessary chats to keep your workspace organized.
      Models Remove Chat Pn

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Switching Between Models

  • Next to the + button is a dropdown menu showing the currently selected model.
  • Click the dropdown menu to select a different AI model and begin a new conversation with it.
    Models Switch Models Pn