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    Solar Pro 2

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    Sold by: Upstage 
    Deployed on AWS
    Free Trial
    Advanced reasoning, tool use, and multilingual support

    Overview

    Solar Pro 2 is Upstage's latest frontier-scale LLM. With just 31B parameters, it delivers top-tier performance through world-class multilingual support, advanced reasoning, and real-world tool use. Especially in Korean, it outperforms much larger models across critical benchmarks. Built for the next generation of practical LLMs, Solar Pro 2 proves that smaller models can still lead.

    Solar Pro 2 supports users and businesses worldwide with its exceptional multilingual processing capabilities. It not only excels in Korean but also demonstrates impressive performance in major language benchmarks for English and Japanese, breaking down global communication barriers. See the table below for Solar Pro 2's outstanding achievements across various key language benchmarks.

    Solar Pro 2 is optimized for intelligent interaction with external tools. Beyond merely understanding language, it acts much like a human, communicating with its environment, thinking autonomously, and executing necessary functions. The example below illustrates how Solar Pro 2 leverages tools in a business environment to transform complex requests into actionable outcomes.

    Highlights

    • **Frontier performance in a compact 31B model**: Delivers top-tier reasoning and problem-solving while keeping model size small - competing with much larger models despite only 31 billion parameters.
    • **Best-in-class Korean & multilingual strength**: Shows exceptional Korean fluency and strong benchmark performance across Korean, English, and Japanese, matching or surpassing much larger top-tier models on key tasks.
    • **Advanced reasoning and tool use for agent-like workflows**: Optimized for multi-step reasoning, complex math/code tasks, and seamless interaction with external tools to support real-world, agent-style enterprise workflows.

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Pricing

    Free trial

    Try this product free for 7 days according to the free trial terms set by the vendor.
    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (3)

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    Dimension
    Description
    Cost/host/hour
    ml.m5.12xlarge Inference (Batch)
    Recommended
    Model inference on the ml.m5.12xlarge instance type, batch mode
    $0.00
    ml.p5.48xlarge Inference (Real-Time)
    Recommended
    Model inference on the ml.p5.48xlarge instance type, real-time mode
    $12.00
    ml.p4d.24xlarge Inference (Real-Time)
    Model inference on the ml.p4d.24xlarge instance type, real-time mode
    $6.40

    Vendor refund policy

    We do not support any refunds currently.

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    Usage information

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    Delivery details

    Amazon SageMaker model

    An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.

    Deploy the model on Amazon SageMaker AI using the following options:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    We have enhanced the stability of containers during the initial bootstrapping process.

    Additional details

    Inputs

    Summary

    We support a request payload that is compatible with OpenAI's chat completion endpoint. You can check the detail input paramter descrption at https://console.upstage.ai/api/chat  .

    Input MIME type
    application/json
    { "model": "solar-pro2", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "Tell me a single joke." } ], "temperature": 0.7 }
    BATCH INFERENCE IS NOT SUPPORTED NOW

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